mtg / effnet-discogs
An EfficientNet for music style classification by 400 styles from the Discogs taxonomy
Prediction
mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabbIDilv7bnj5bfgwtoke63aez7v6yuStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- top_n
- "10"
- output_format
- Visualization
{ "audio": "https://replicate.delivery/mgxm/d8b7b2b3-6c04-4ffe-b6fe-a53f8768e217/rock.mp3", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", { input: { audio: "https://replicate.delivery/mgxm/d8b7b2b3-6c04-4ffe-b6fe-a53f8768e217/rock.mp3", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", input={ "audio": "https://replicate.delivery/mgxm/d8b7b2b3-6c04-4ffe-b6fe-a53f8768e217/rock.mp3", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", "input": { "audio": "https://replicate.delivery/mgxm/d8b7b2b3-6c04-4ffe-b6fe-a53f8768e217/rock.mp3", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-03-15T14:38:47.283348Z", "created_at": "2022-03-15T14:38:13.165490Z", "data_removed": false, "error": null, "id": "ilv7bnj5bfgwtoke63aez7v6yu", "input": { "audio": "https://replicate.delivery/mgxm/d8b7b2b3-6c04-4ffe-b6fe-a53f8768e217/rock.mp3", "top_n": "10", "output_format": "Visualization" }, "logs": "running the inference network...\n2022-03-15 14:38:41.044365: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\nplotting...\ndone!", "metrics": { "predict_time": 7.112829, "total_time": 34.117858 }, "output": "https://replicate.delivery/mgxm/e866d896-48f5-4cb5-b69d-13f724f8ea80/out.png", "started_at": "2022-03-15T14:38:40.170519Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ilv7bnj5bfgwtoke63aez7v6yu", "cancel": "https://api.replicate.com/v1/predictions/ilv7bnj5bfgwtoke63aez7v6yu/cancel" }, "version": "3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb" }Generated inrunning the inference network... 2022-03-15 14:38:41.044365: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz plotting... done!Prediction
mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabbID6p4ce32gpbeqzgmmarn226dbk4StatusSucceededSourceWebHardware–Total durationCreatedInput
- url
- https://www.youtube.com/watch?v=hZ8Bc6jz-W8
- top_n
- "10"
- output_format
- Visualization
{ "url": "https://www.youtube.com/watch?v=hZ8Bc6jz-W8", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", { input: { url: "https://www.youtube.com/watch?v=hZ8Bc6jz-W8", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", input={ "url": "https://www.youtube.com/watch?v=hZ8Bc6jz-W8", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", "input": { "url": "https://www.youtube.com/watch?v=hZ8Bc6jz-W8", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-03-16T11:44:10.963398Z", "created_at": "2022-03-16T11:41:31.403371Z", "data_removed": false, "error": null, "id": "6p4ce32gpbeqzgmmarn226dbk4", "input": { "url": "https://www.youtube.com/watch?v=hZ8Bc6jz-W8", "top_n": "10", "output_format": "Visualization" }, "logs": "[youtube] hZ8Bc6jz-W8: Downloading webpage\n[youtube] hZ8Bc6jz-W8: Downloading player bd67d609\n[download] Destination: /tmp/tmpx0pzfidb/audio.webm\n\n[download] 0.0% of 3.56MiB at 7.74KiB/s ETA 07:50\n[download] 0.1% of 3.56MiB at 23.19KiB/s ETA 02:37\n[download] 0.2% of 3.56MiB at 54.08KiB/s ETA 01:07\n[download] 0.4% of 3.56MiB at 115.77KiB/s ETA 00:31\n[download] 0.9% of 3.56MiB at 93.41KiB/s ETA 00:38\n[download] 1.7% of 3.56MiB at 81.28KiB/s ETA 00:44\n[download] 3.5% of 3.56MiB at 76.15KiB/s ETA 00:46\n[download] 5.5% of 3.56MiB at 72.06KiB/s ETA 00:47\n[download] 7.3% of 3.56MiB at 72.96KiB/s ETA 00:46\n[download] 9.3% of 3.56MiB at 72.17KiB/s ETA 00:45\n[download] 11.2% of 3.56MiB at 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3.56MiB at 73.41KiB/s ETA 00:24\n[download] 52.1% of 3.56MiB at 73.49KiB/s ETA 00:23\n[download] 54.2% of 3.56MiB at 73.31KiB/s ETA 00:22\n[download] 56.1% of 3.56MiB at 73.51KiB/s ETA 00:21\n[download] 58.2% of 3.56MiB at 73.50KiB/s ETA 00:20\n[download] 60.2% of 3.56MiB at 73.26KiB/s ETA 00:19\n[download] 62.1% of 3.56MiB at 73.38KiB/s ETA 00:18\n[download] 64.2% of 3.56MiB at 73.29KiB/s ETA 00:17\n[download] 66.2% of 3.56MiB at 73.45KiB/s ETA 00:16\n[download] 68.3% of 3.56MiB at 73.41KiB/s ETA 00:15\n[download] 70.3% of 3.56MiB at 73.18KiB/s ETA 00:14\n[download] 72.1% of 3.56MiB at 73.22KiB/s ETA 00:13\n[download] 74.2% of 3.56MiB at 73.51KiB/s ETA 00:12\n[download] 76.5% of 3.56MiB at 73.24KiB/s ETA 00:11\n[download] 78.3% of 3.56MiB at 73.28KiB/s ETA 00:10\n[download] 80.4% of 3.56MiB at 73.20KiB/s ETA 00:09\n[download] 82.3% of 3.56MiB at 73.36KiB/s ETA 00:08\n[download] 84.5% of 3.56MiB at 73.38KiB/s ETA 00:07\n[download] 86.6% of 3.56MiB at 73.25KiB/s ETA 00:06\n[download] 88.4% of 3.56MiB at 73.35KiB/s ETA 00:05\n[download] 90.6% of 3.56MiB at 73.32KiB/s ETA 00:04\n[download] 92.6% of 3.56MiB at 73.50KiB/s ETA 00:03\n[download] 94.8% of 3.56MiB at 73.24KiB/s ETA 00:02\n[download] 96.6% of 3.56MiB at 73.26KiB/s ETA 00:01\n[download] 98.6% of 3.56MiB at 73.47KiB/s ETA 00:00\n[download] 100.0% of 3.56MiB at 73.58KiB/s ETA 00:00\n[download] 100% of 3.56MiB in 00:49\n[ffmpeg] Destination: /tmp/tmpx0pzfidb/audio.wav\nDeleting original file /tmp/tmpx0pzfidb/audio.webm (pass -k to keep)\nrunning the inference network...\n2022-03-16 11:44:04.696891: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\nplotting...\ndone!", "metrics": { "predict_time": 59.641277, "total_time": 159.560027 }, "output": "https://replicate.delivery/mgxm/6eb9f83d-9e3d-417c-94fb-0f17b58993c5/out.png", "started_at": "2022-03-16T11:43:11.322121Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6p4ce32gpbeqzgmmarn226dbk4", "cancel": "https://api.replicate.com/v1/predictions/6p4ce32gpbeqzgmmarn226dbk4/cancel" }, "version": "3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb" }Generated in[youtube] hZ8Bc6jz-W8: Downloading webpage [youtube] hZ8Bc6jz-W8: Downloading player bd67d609 [download] Destination: /tmp/tmpx0pzfidb/audio.webm [download] 0.0% of 3.56MiB at 7.74KiB/s ETA 07:50 [download] 0.1% of 3.56MiB at 23.19KiB/s ETA 02:37 [download] 0.2% of 3.56MiB at 54.08KiB/s ETA 01:07 [download] 0.4% of 3.56MiB at 115.77KiB/s ETA 00:31 [download] 0.9% of 3.56MiB at 93.41KiB/s ETA 00:38 [download] 1.7% of 3.56MiB at 81.28KiB/s ETA 00:44 [download] 3.5% of 3.56MiB at 76.15KiB/s ETA 00:46 [download] 5.5% of 3.56MiB at 72.06KiB/s ETA 00:47 [download] 7.3% of 3.56MiB at 72.96KiB/s ETA 00:46 [download] 9.3% of 3.56MiB at 72.17KiB/s ETA 00:45 [download] 11.2% of 3.56MiB at 73.06KiB/s ETA 00:44 [download] 13.4% of 3.56MiB at 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[download] 92.6% of 3.56MiB at 73.50KiB/s ETA 00:03 [download] 94.8% of 3.56MiB at 73.24KiB/s ETA 00:02 [download] 96.6% of 3.56MiB at 73.26KiB/s ETA 00:01 [download] 98.6% of 3.56MiB at 73.47KiB/s ETA 00:00 [download] 100.0% of 3.56MiB at 73.58KiB/s ETA 00:00 [download] 100% of 3.56MiB in 00:49 [ffmpeg] Destination: /tmp/tmpx0pzfidb/audio.wav Deleting original file /tmp/tmpx0pzfidb/audio.webm (pass -k to keep) running the inference network... 2022-03-16 11:44:04.696891: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz plotting... done!Prediction
mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfbIDqk6vgajzgnebbjfnn53pconrlaStatusSucceededSourceWebHardware–Total durationCreatedInput
- url
- https://www.youtube.com/watch?v=S7bOg3oercg
- top_n
- "10"
- output_format
- Visualization
{ "url": "https://www.youtube.com/watch?v=S7bOg3oercg", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", { input: { url: "https://www.youtube.com/watch?v=S7bOg3oercg", top_n: "10", output_format: "Visualization" } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", input={ "url": "https://www.youtube.com/watch?v=S7bOg3oercg", "top_n": "10", "output_format": "Visualization" } ) # The mtg/effnet-discogs model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/mtg/effnet-discogs/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", "input": { "url": "https://www.youtube.com/watch?v=S7bOg3oercg", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-12-10T15:58:37.147969Z", "created_at": "2021-12-10T15:56:11.606515Z", "data_removed": false, "error": null, "id": "qk6vgajzgnebbjfnn53pconrla", "input": { "url": "https://www.youtube.com/watch?v=S7bOg3oercg", "top_n": "10", "output_format": "Visualization" }, "logs": "[youtube] S7bOg3oercg: Downloading webpage\n[youtube] S7bOg3oercg: Downloading player a515f6d1\n[download] Destination: /tmp/tmpg62ovc3u/audio.webm\n\n[download] 0.0% of 5.33MiB at 6.35KiB/s ETA 14:19\n[download] 0.1% of 5.33MiB at 19.02KiB/s ETA 04:46\n[download] 0.1% of 5.33MiB at 44.36KiB/s ETA 02:02\n[download] 0.3% of 5.33MiB at 94.99KiB/s ETA 00:57\n[download] 0.6% of 5.33MiB at 76.42KiB/s ETA 01:10\n[download] 1.2% of 5.33MiB at 66.49KiB/s ETA 01:21\n[download] 2.2% of 5.33MiB at 60.77KiB/s ETA 01:27\n[download] 3.3% of 5.33MiB at 57.90KiB/s ETA 01:31\n[download] 4.2% of 5.33MiB at 59.64KiB/s ETA 01:27\n[download] 5.4% of 5.33MiB at 60.28KiB/s ETA 01:25\n[download] 6.6% of 5.33MiB at 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"metrics": { "predict_time": 139.203567, "total_time": 145.541454 }, "output": [ { "file": "https://replicate.delivery/mgxm/b6be3ebf-1bf7-4a6f-970f-0a19dd3b3e07/out.png" } ], "started_at": "2021-12-10T15:56:17.944402Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/qk6vgajzgnebbjfnn53pconrla", "cancel": "https://api.replicate.com/v1/predictions/qk6vgajzgnebbjfnn53pconrla/cancel" }, "version": "3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb" }Generated in[youtube] S7bOg3oercg: Downloading webpage [youtube] S7bOg3oercg: Downloading player a515f6d1 [download] Destination: /tmp/tmpg62ovc3u/audio.webm [download] 0.0% of 5.33MiB at 6.35KiB/s ETA 14:19 [download] 0.1% of 5.33MiB at 19.02KiB/s ETA 04:46 [download] 0.1% of 5.33MiB at 44.36KiB/s ETA 02:02 [download] 0.3% of 5.33MiB at 94.99KiB/s ETA 00:57 [download] 0.6% of 5.33MiB at 76.42KiB/s ETA 01:10 [download] 1.2% of 5.33MiB at 66.49KiB/s ETA 01:21 [download] 2.2% of 5.33MiB at 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[ INFO ] On connection TensorflowInputMusiCNN::bands → VectorRealToTensor::frame: [ INFO ] BUFFER SIZE MISMATCH: max=0 - asked for read size 128 [ INFO ] resizing buffer to 1120/140 2021-12-10 15:57:55.142243: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz plotting... done!Prediction
mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfbIDxurrhvvohjglbd6q4jld4jlszuStatusSucceededSourceWebHardware–Total durationCreatedInput
- url
- https://www.youtube.com/watch?v=pAgnJDJN4VA
- top_n
- "10"
- output_format
- Visualization
{ "url": "https://www.youtube.com/watch?v=pAgnJDJN4VA", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", { input: { url: "https://www.youtube.com/watch?v=pAgnJDJN4VA", top_n: "10", output_format: "Visualization" } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", input={ "url": "https://www.youtube.com/watch?v=pAgnJDJN4VA", "top_n": "10", "output_format": "Visualization" } ) # The mtg/effnet-discogs model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/mtg/effnet-discogs/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", "input": { "url": "https://www.youtube.com/watch?v=pAgnJDJN4VA", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-12-10T16:12:57.488340Z", "created_at": "2021-12-10T16:11:28.300051Z", "data_removed": false, "error": null, "id": "xurrhvvohjglbd6q4jld4jlszu", "input": { "url": "https://www.youtube.com/watch?v=pAgnJDJN4VA", "top_n": "10", "output_format": "Visualization" }, "logs": "[youtube] pAgnJDJN4VA: Downloading webpage\n[youtube] pAgnJDJN4VA: Downloading player a515f6d1\n[download] Destination: /tmp/tmpy3o0ytc9/audio.webm\n\n[download] 0.0% of 3.83MiB at 8.87KiB/s ETA 07:21\n[download] 0.1% of 3.83MiB at 26.56KiB/s ETA 02:27\n[download] 0.2% of 3.83MiB at 61.91KiB/s ETA 01:03\n[download] 0.4% of 3.83MiB at 132.55KiB/s ETA 00:29\n[download] 0.8% of 3.83MiB at 106.85KiB/s ETA 00:36\n[download] 1.6% of 3.83MiB at 92.96KiB/s ETA 00:41\n[download] 3.2% of 3.83MiB at 88.40KiB/s ETA 00:42\n[download] 5.4% of 3.83MiB at 82.33KiB/s ETA 00:45\n[download] 7.3% of 3.83MiB at 85.41KiB/s ETA 00:42\n[download] 9.7% of 3.83MiB at 84.87KiB/s ETA 00:41\n[download] 11.9% of 3.83MiB at 82.32KiB/s ETA 00:41\n[download] 13.7% of 3.83MiB at 83.87KiB/s ETA 00:40\n[download] 16.1% of 3.83MiB at 83.95KiB/s ETA 00:39\n[download] 18.3% of 3.83MiB at 84.48KiB/s ETA 00:37\n[download] 20.6% of 3.83MiB at 83.76KiB/s ETA 00:37\n[download] 22.6% of 3.83MiB at 83.63KiB/s ETA 00:36\n[download] 24.7% of 3.83MiB at 83.86KiB/s ETA 00:35\n[download] 26.9% of 3.83MiB at 84.25KiB/s ETA 00:33\n[download] 29.1% of 3.83MiB at 83.79KiB/s ETA 00:33\n[download] 31.2% of 3.83MiB at 83.71KiB/s ETA 00:32\n[download] 33.3% of 3.83MiB at 83.89KiB/s ETA 00:31\n[download] 35.5% of 3.83MiB at 84.39KiB/s ETA 00:29\n[download] 37.8% of 3.83MiB at 84.08KiB/s ETA 00:28\n[download] 39.9% of 3.83MiB at 84.05KiB/s ETA 00:28\n[download] 42.0% of 3.83MiB at 84.31KiB/s ETA 00:26\n[download] 44.3% of 3.83MiB at 83.95KiB/s ETA 00:25\n[download] 46.3% of 3.83MiB at 83.86KiB/s ETA 00:25\n[download] 48.4% of 3.83MiB at 83.99KiB/s ETA 00:24\n[download] 50.6% of 3.83MiB at 84.29KiB/s ETA 00:22\n[download] 52.9% of 3.83MiB at 84.07KiB/s ETA 00:21\n[download] 55.0% of 3.83MiB at 84.11KiB/s ETA 00:20\n[download] 57.1% of 3.83MiB at 84.29KiB/s ETA 00:19\n[download] 59.4% of 3.83MiB at 84.03KiB/s ETA 00:18\n[download] 61.4% of 3.83MiB at 83.95KiB/s ETA 00:18\n[download] 63.5% of 3.83MiB at 84.06KiB/s ETA 00:17\n[download] 65.7% of 3.83MiB at 84.30KiB/s ETA 00:15\n[download] 68.0% of 3.83MiB at 84.14KiB/s ETA 00:14\n[download] 70.1% of 3.83MiB at 84.18KiB/s ETA 00:13\n[download] 72.3% of 3.83MiB at 84.33KiB/s ETA 00:12\n[download] 74.6% of 3.83MiB at 84.13KiB/s ETA 00:11\n[download] 76.6% of 3.83MiB at 84.11KiB/s ETA 00:10\n[download] 78.7% of 3.83MiB at 84.21KiB/s ETA 00:09\n[download] 80.9% of 3.83MiB at 83.97KiB/s ETA 00:08\n[download] 82.9% of 3.83MiB at 84.29KiB/s ETA 00:07\n[download] 85.4% of 3.83MiB at 84.01KiB/s ETA 00:06\n[download] 87.4% of 3.83MiB at 84.31KiB/s ETA 00:05\n[download] 89.9% of 3.83MiB at 84.03KiB/s ETA 00:04\n[download] 91.8% of 3.83MiB at 84.30KiB/s ETA 00:03\n[download] 94.4% of 3.83MiB at 84.03KiB/s ETA 00:02\n[download] 96.3% of 3.83MiB at 84.28KiB/s ETA 00:01\n[download] 98.8% of 3.83MiB at 84.33KiB/s ETA 00:00\n[download] 100.0% of 3.83MiB at 84.35KiB/s ETA 00:00\n[download] 100% of 3.83MiB in 00:46\n[ffmpeg] Destination: /tmp/tmpy3o0ytc9/audio.wav\nDeleting original file /tmp/tmpy3o0ytc9/audio.webm (pass -k to keep)\nrunning the inference network...\n[ INFO ] On connection TensorflowInputMusiCNN::bands → VectorRealToTensor::frame:\n[ INFO ] BUFFER SIZE MISMATCH: max=0 - asked for read size 128\n[ INFO ] resizing buffer to 1120/140\n2021-12-10 16:12:26.009956: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\nplotting...\ndone!", "metrics": { "predict_time": 81.973588, "total_time": 89.188289 }, "output": [ { "file": "https://replicate.delivery/mgxm/35f9c812-5af6-4371-bd46-89b68c4c454a/out.png" } ], "started_at": "2021-12-10T16:11:35.514752Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xurrhvvohjglbd6q4jld4jlszu", "cancel": "https://api.replicate.com/v1/predictions/xurrhvvohjglbd6q4jld4jlszu/cancel" }, "version": "3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb" }Generated in[youtube] pAgnJDJN4VA: Downloading webpage [youtube] pAgnJDJN4VA: Downloading player a515f6d1 [download] Destination: /tmp/tmpy3o0ytc9/audio.webm [download] 0.0% of 3.83MiB at 8.87KiB/s ETA 07:21 [download] 0.1% of 3.83MiB at 26.56KiB/s ETA 02:27 [download] 0.2% of 3.83MiB at 61.91KiB/s ETA 01:03 [download] 0.4% of 3.83MiB at 132.55KiB/s ETA 00:29 [download] 0.8% of 3.83MiB at 106.85KiB/s ETA 00:36 [download] 1.6% of 3.83MiB at 92.96KiB/s ETA 00:41 [download] 3.2% of 3.83MiB at 88.40KiB/s ETA 00:42 [download] 5.4% of 3.83MiB at 82.33KiB/s ETA 00:45 [download] 7.3% of 3.83MiB at 85.41KiB/s ETA 00:42 [download] 9.7% of 3.83MiB at 84.87KiB/s ETA 00:41 [download] 11.9% of 3.83MiB at 82.32KiB/s ETA 00:41 [download] 13.7% of 3.83MiB at 83.87KiB/s ETA 00:40 [download] 16.1% of 3.83MiB at 83.95KiB/s ETA 00:39 [download] 18.3% of 3.83MiB at 84.48KiB/s ETA 00:37 [download] 20.6% of 3.83MiB at 83.76KiB/s ETA 00:37 [download] 22.6% of 3.83MiB at 83.63KiB/s ETA 00:36 [download] 24.7% of 3.83MiB at 83.86KiB/s ETA 00:35 [download] 26.9% of 3.83MiB at 84.25KiB/s ETA 00:33 [download] 29.1% of 3.83MiB at 83.79KiB/s ETA 00:33 [download] 31.2% of 3.83MiB at 83.71KiB/s ETA 00:32 [download] 33.3% of 3.83MiB at 83.89KiB/s ETA 00:31 [download] 35.5% of 3.83MiB at 84.39KiB/s ETA 00:29 [download] 37.8% of 3.83MiB at 84.08KiB/s ETA 00:28 [download] 39.9% of 3.83MiB at 84.05KiB/s ETA 00:28 [download] 42.0% of 3.83MiB at 84.31KiB/s ETA 00:26 [download] 44.3% of 3.83MiB at 83.95KiB/s ETA 00:25 [download] 46.3% of 3.83MiB at 83.86KiB/s ETA 00:25 [download] 48.4% of 3.83MiB at 83.99KiB/s ETA 00:24 [download] 50.6% of 3.83MiB at 84.29KiB/s ETA 00:22 [download] 52.9% of 3.83MiB at 84.07KiB/s ETA 00:21 [download] 55.0% of 3.83MiB at 84.11KiB/s ETA 00:20 [download] 57.1% of 3.83MiB at 84.29KiB/s ETA 00:19 [download] 59.4% of 3.83MiB at 84.03KiB/s ETA 00:18 [download] 61.4% of 3.83MiB at 83.95KiB/s ETA 00:18 [download] 63.5% of 3.83MiB at 84.06KiB/s ETA 00:17 [download] 65.7% of 3.83MiB at 84.30KiB/s ETA 00:15 [download] 68.0% of 3.83MiB at 84.14KiB/s ETA 00:14 [download] 70.1% of 3.83MiB at 84.18KiB/s ETA 00:13 [download] 72.3% of 3.83MiB at 84.33KiB/s ETA 00:12 [download] 74.6% of 3.83MiB at 84.13KiB/s ETA 00:11 [download] 76.6% of 3.83MiB at 84.11KiB/s ETA 00:10 [download] 78.7% of 3.83MiB at 84.21KiB/s ETA 00:09 [download] 80.9% of 3.83MiB at 83.97KiB/s ETA 00:08 [download] 82.9% of 3.83MiB at 84.29KiB/s ETA 00:07 [download] 85.4% of 3.83MiB at 84.01KiB/s ETA 00:06 [download] 87.4% of 3.83MiB at 84.31KiB/s ETA 00:05 [download] 89.9% of 3.83MiB at 84.03KiB/s ETA 00:04 [download] 91.8% of 3.83MiB at 84.30KiB/s ETA 00:03 [download] 94.4% of 3.83MiB at 84.03KiB/s ETA 00:02 [download] 96.3% of 3.83MiB at 84.28KiB/s ETA 00:01 [download] 98.8% of 3.83MiB at 84.33KiB/s ETA 00:00 [download] 100.0% of 3.83MiB at 84.35KiB/s ETA 00:00 [download] 100% of 3.83MiB in 00:46 [ffmpeg] Destination: /tmp/tmpy3o0ytc9/audio.wav Deleting original file /tmp/tmpy3o0ytc9/audio.webm (pass -k to keep) running the inference network... [ INFO ] On connection TensorflowInputMusiCNN::bands → VectorRealToTensor::frame: [ INFO ] BUFFER SIZE MISMATCH: max=0 - asked for read size 128 [ INFO ] resizing buffer to 1120/140 2021-12-10 16:12:26.009956: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz plotting... done!Prediction
mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfbID7be24mwdvvbtdmvcw7jizcmn3yStatusSucceededSourceWebHardware–Total durationCreatedInput
- url
- https://www.youtube.com/watch?v=SBjQ9tuuTJQ
- top_n
- "10"
- output_format
- Visualization
{ "url": "https://www.youtube.com/watch?v=SBjQ9tuuTJQ", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", { input: { url: "https://www.youtube.com/watch?v=SBjQ9tuuTJQ", top_n: "10", output_format: "Visualization" } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", input={ "url": "https://www.youtube.com/watch?v=SBjQ9tuuTJQ", "top_n": "10", "output_format": "Visualization" } ) # The mtg/effnet-discogs model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/mtg/effnet-discogs/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb", "input": { "url": "https://www.youtube.com/watch?v=SBjQ9tuuTJQ", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2021-12-10T17:07:38.101216Z", "created_at": "2021-12-10T17:06:01.455962Z", "data_removed": false, "error": null, "id": "7be24mwdvvbtdmvcw7jizcmn3y", "input": { "url": "https://www.youtube.com/watch?v=SBjQ9tuuTJQ", "top_n": "10", "output_format": "Visualization" }, "logs": "[youtube] SBjQ9tuuTJQ: Downloading webpage\n[youtube] SBjQ9tuuTJQ: Downloading player a515f6d1\n[download] Destination: /tmp/tmpvy8j42i8/audio.webm\n\n[download] 0.0% of 4.18MiB at 8.78KiB/s ETA 08:07\n[download] 0.1% of 4.18MiB at 26.29KiB/s ETA 02:42\n[download] 0.2% of 4.18MiB at 61.30KiB/s ETA 01:09\n[download] 0.4% of 4.18MiB at 131.24KiB/s ETA 00:32\n[download] 0.7% of 4.18MiB at 105.63KiB/s ETA 00:40\n[download] 1.5% of 4.18MiB at 91.85KiB/s ETA 00:45\n[download] 3.0% of 4.18MiB at 87.32KiB/s ETA 00:47\n[download] 4.9% of 4.18MiB at 80.91KiB/s ETA 00:50\n[download] 6.6% of 4.18MiB at 84.05KiB/s ETA 00:47\n[download] 8.8% of 4.18MiB at 83.42KiB/s ETA 00:46\n[download] 10.7% of 4.18MiB at 83.62KiB/s ETA 00:45\n[download] 12.7% of 4.18MiB at 84.22KiB/s ETA 00:44\n[download] 14.7% of 4.18MiB at 82.90KiB/s ETA 00:44\n[download] 16.5% of 4.18MiB at 82.39KiB/s ETA 00:43\n[download] 18.3% of 4.18MiB at 82.27KiB/s ETA 00:42\n[download] 20.2% of 4.18MiB at 82.41KiB/s ETA 00:41\n[download] 22.2% of 4.18MiB at 82.77KiB/s ETA 00:40\n[download] 24.2% of 4.18MiB at 83.33KiB/s ETA 00:38\n[download] 26.3% of 4.18MiB at 82.53KiB/s ETA 00:38\n[download] 28.1% of 4.18MiB at 82.44KiB/s ETA 00:37\n[download] 30.0% of 4.18MiB at 82.52KiB/s ETA 00:36\n[download] 31.9% of 4.18MiB at 82.77KiB/s ETA 00:35\n[download] 33.9% of 4.18MiB at 83.24KiB/s ETA 00:33\n[download] 36.1% of 4.18MiB at 82.97KiB/s ETA 00:32\n[download] 37.9% of 4.18MiB at 82.91KiB/s ETA 00:32\n[download] 39.8% of 4.18MiB at 83.06KiB/s ETA 00:31\n[download] 41.8% of 4.18MiB at 83.33KiB/s ETA 00:29\n[download] 43.9% of 4.18MiB at 82.99KiB/s ETA 00:28\n[download] 45.7% of 4.18MiB at 82.91KiB/s ETA 00:28\n[download] 47.6% of 4.18MiB at 82.94KiB/s ETA 00:27\n[download] 49.6% of 4.18MiB at 83.09KiB/s ETA 00:25\n[download] 51.6% of 4.18MiB at 82.79KiB/s ETA 00:25\n[download] 53.4% of 4.18MiB at 83.24KiB/s ETA 00:23\n[download] 55.7% of 4.18MiB at 83.31KiB/s ETA 00:22\n[download] 57.7% of 4.18MiB at 82.93KiB/s ETA 00:21\n[download] 59.4% of 4.18MiB at 83.24KiB/s ETA 00:20\n[download] 61.6% of 4.18MiB at 83.21KiB/s ETA 00:19\n[download] 63.5% of 4.18MiB at 83.21KiB/s ETA 00:18\n[download] 65.5% of 4.18MiB at 82.80KiB/s ETA 00:17\n[download] 67.1% of 4.18MiB at 82.90KiB/s ETA 00:16\n[download] 69.2% of 4.18MiB at 82.71KiB/s ETA 00:15\n[download] 71.0% of 4.18MiB at 83.07KiB/s ETA 00:14\n[download] 73.3% of 4.18MiB at 82.73KiB/s ETA 00:13\n[download] 75.0% of 4.18MiB at 82.99KiB/s ETA 00:12\n[download] 77.3% of 4.18MiB at 82.98KiB/s ETA 00:11\n[download] 79.2% of 4.18MiB at 83.08KiB/s ETA 00:10\n[download] 81.2% of 4.18MiB at 82.86KiB/s ETA 00:09\n[download] 83.0% of 4.18MiB at 82.74KiB/s ETA 00:08\n[download] 84.8% of 4.18MiB at 83.06KiB/s ETA 00:07\n[download] 87.1% of 4.18MiB at 82.82KiB/s ETA 00:06\n[download] 88.9% of 4.18MiB at 83.08KiB/s ETA 00:05\n[download] 91.2% of 4.18MiB at 82.79KiB/s ETA 00:04\n[download] 92.9% of 4.18MiB at 82.99KiB/s ETA 00:03\n[download] 95.1% of 4.18MiB at 82.89KiB/s ETA 00:02\n[download] 97.0% of 4.18MiB at 82.90KiB/s ETA 00:01\n[download] 98.9% of 4.18MiB at 82.96KiB/s ETA 00:00\n[download] 100.0% of 4.18MiB at 83.04KiB/s ETA 00:00\n[download] 100% of 4.18MiB in 00:51\n[ffmpeg] Destination: /tmp/tmpvy8j42i8/audio.wav\nDeleting original file /tmp/tmpvy8j42i8/audio.webm (pass -k to keep)\nrunning the inference network...\n[ INFO ] On connection TensorflowInputMusiCNN::bands → VectorRealToTensor::frame:\n[ INFO ] BUFFER SIZE MISMATCH: max=0 - asked for read size 128\n[ INFO ] resizing buffer to 1120/140\n2021-12-10 17:07:05.372099: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\nplotting...\ndone!", "metrics": { "predict_time": 90.27851, "total_time": 96.645254 }, "output": [ { "file": "https://replicate.delivery/mgxm/cca8f3fb-4844-443e-9cdd-81e82a64b8fe/out.png" } ], "started_at": "2021-12-10T17:06:07.822706Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7be24mwdvvbtdmvcw7jizcmn3y", "cancel": "https://api.replicate.com/v1/predictions/7be24mwdvvbtdmvcw7jizcmn3y/cancel" }, "version": "3030f474fca76dbe7fc4d1440860510a1aea2b30e72fd7a11f1e273307853bfb" }Generated in[youtube] SBjQ9tuuTJQ: Downloading webpage [youtube] SBjQ9tuuTJQ: Downloading player a515f6d1 [download] Destination: /tmp/tmpvy8j42i8/audio.webm [download] 0.0% of 4.18MiB at 8.78KiB/s ETA 08:07 [download] 0.1% of 4.18MiB at 26.29KiB/s ETA 02:42 [download] 0.2% of 4.18MiB at 61.30KiB/s ETA 01:09 [download] 0.4% of 4.18MiB at 131.24KiB/s ETA 00:32 [download] 0.7% of 4.18MiB at 105.63KiB/s ETA 00:40 [download] 1.5% of 4.18MiB at 91.85KiB/s ETA 00:45 [download] 3.0% of 4.18MiB at 87.32KiB/s ETA 00:47 [download] 4.9% of 4.18MiB at 80.91KiB/s ETA 00:50 [download] 6.6% of 4.18MiB at 84.05KiB/s ETA 00:47 [download] 8.8% of 4.18MiB at 83.42KiB/s ETA 00:46 [download] 10.7% of 4.18MiB at 83.62KiB/s ETA 00:45 [download] 12.7% of 4.18MiB at 84.22KiB/s ETA 00:44 [download] 14.7% of 4.18MiB at 82.90KiB/s ETA 00:44 [download] 16.5% of 4.18MiB at 82.39KiB/s ETA 00:43 [download] 18.3% of 4.18MiB at 82.27KiB/s ETA 00:42 [download] 20.2% of 4.18MiB at 82.41KiB/s ETA 00:41 [download] 22.2% of 4.18MiB at 82.77KiB/s ETA 00:40 [download] 24.2% of 4.18MiB at 83.33KiB/s ETA 00:38 [download] 26.3% of 4.18MiB at 82.53KiB/s ETA 00:38 [download] 28.1% of 4.18MiB at 82.44KiB/s ETA 00:37 [download] 30.0% of 4.18MiB at 82.52KiB/s ETA 00:36 [download] 31.9% of 4.18MiB at 82.77KiB/s ETA 00:35 [download] 33.9% of 4.18MiB at 83.24KiB/s ETA 00:33 [download] 36.1% of 4.18MiB at 82.97KiB/s ETA 00:32 [download] 37.9% of 4.18MiB at 82.91KiB/s ETA 00:32 [download] 39.8% of 4.18MiB at 83.06KiB/s ETA 00:31 [download] 41.8% of 4.18MiB at 83.33KiB/s ETA 00:29 [download] 43.9% of 4.18MiB at 82.99KiB/s ETA 00:28 [download] 45.7% of 4.18MiB at 82.91KiB/s ETA 00:28 [download] 47.6% of 4.18MiB at 82.94KiB/s ETA 00:27 [download] 49.6% of 4.18MiB at 83.09KiB/s ETA 00:25 [download] 51.6% of 4.18MiB at 82.79KiB/s ETA 00:25 [download] 53.4% of 4.18MiB at 83.24KiB/s ETA 00:23 [download] 55.7% of 4.18MiB at 83.31KiB/s ETA 00:22 [download] 57.7% of 4.18MiB at 82.93KiB/s ETA 00:21 [download] 59.4% of 4.18MiB at 83.24KiB/s ETA 00:20 [download] 61.6% of 4.18MiB at 83.21KiB/s ETA 00:19 [download] 63.5% of 4.18MiB at 83.21KiB/s ETA 00:18 [download] 65.5% of 4.18MiB at 82.80KiB/s ETA 00:17 [download] 67.1% of 4.18MiB at 82.90KiB/s ETA 00:16 [download] 69.2% of 4.18MiB at 82.71KiB/s ETA 00:15 [download] 71.0% of 4.18MiB at 83.07KiB/s ETA 00:14 [download] 73.3% of 4.18MiB at 82.73KiB/s ETA 00:13 [download] 75.0% of 4.18MiB at 82.99KiB/s ETA 00:12 [download] 77.3% of 4.18MiB at 82.98KiB/s ETA 00:11 [download] 79.2% of 4.18MiB at 83.08KiB/s ETA 00:10 [download] 81.2% of 4.18MiB at 82.86KiB/s ETA 00:09 [download] 83.0% of 4.18MiB at 82.74KiB/s ETA 00:08 [download] 84.8% of 4.18MiB at 83.06KiB/s ETA 00:07 [download] 87.1% of 4.18MiB at 82.82KiB/s ETA 00:06 [download] 88.9% of 4.18MiB at 83.08KiB/s ETA 00:05 [download] 91.2% of 4.18MiB at 82.79KiB/s ETA 00:04 [download] 92.9% of 4.18MiB at 82.99KiB/s ETA 00:03 [download] 95.1% of 4.18MiB at 82.89KiB/s ETA 00:02 [download] 97.0% of 4.18MiB at 82.90KiB/s ETA 00:01 [download] 98.9% of 4.18MiB at 82.96KiB/s ETA 00:00 [download] 100.0% of 4.18MiB at 83.04KiB/s ETA 00:00 [download] 100% of 4.18MiB in 00:51 [ffmpeg] Destination: /tmp/tmpvy8j42i8/audio.wav Deleting original file /tmp/tmpvy8j42i8/audio.webm (pass -k to keep) running the inference network... [ INFO ] On connection TensorflowInputMusiCNN::bands → VectorRealToTensor::frame: [ INFO ] BUFFER SIZE MISMATCH: max=0 - asked for read size 128 [ INFO ] resizing buffer to 1120/140 2021-12-10 17:07:05.372099: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz plotting... done!Prediction
mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabbInput
- url
- https://www.youtube.com/watch?v=CHekNnySAfM
- top_n
- "10"
- output_format
- Visualization
{ "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", { input: { url: "https://www.youtube.com/watch?v=CHekNnySAfM", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", input={ "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", "input": { "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-03-16T13:56:03.874572Z", "created_at": "2022-03-16T13:54:24.327306Z", "data_removed": false, "error": null, "id": "mnjyyydfrjdwjp7jtsfj2gnysm", "input": { "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "top_n": "10", "output_format": "Visualization" }, "logs": "[youtube] CHekNnySAfM: Downloading webpage\n[youtube] CHekNnySAfM: Downloading player bd67d609\n[download] Destination: /tmp/tmp5hp8fkyh/audio.webm\n\n[download] 0.0% of 3.82MiB at 7.33KiB/s ETA 08:53\n[download] 0.1% of 3.82MiB at 21.97KiB/s ETA 02:57\n[download] 0.2% of 3.82MiB at 51.24KiB/s ETA 01:16\n[download] 0.4% of 3.82MiB at 109.68KiB/s ETA 00:35\n[download] 0.8% of 3.82MiB at 88.27KiB/s ETA 00:43\n[download] 1.6% of 3.82MiB at 76.81KiB/s ETA 00:50\n[download] 3.2% of 3.82MiB at 73.03KiB/s ETA 00:51\n[download] 5.0% of 3.82MiB at 68.01KiB/s ETA 00:54\n[download] 6.6% of 3.82MiB at 67.48KiB/s ETA 00:54\n[download] 8.3% of 3.82MiB at 68.29KiB/s ETA 00:52\n[download] 10.1% of 3.82MiB at 69.88KiB/s ETA 00:50\n[download] 12.1% of 3.82MiB at 69.50KiB/s ETA 00:49\n[download] 13.8% of 3.82MiB at 70.00KiB/s ETA 00:48\n[download] 15.7% of 3.82MiB at 69.33KiB/s ETA 00:47\n[download] 17.3% of 3.82MiB at 69.45KiB/s ETA 00:46\n[download] 19.2% of 3.82MiB at 70.08KiB/s ETA 00:45\n[download] 21.1% of 3.82MiB at 69.75KiB/s ETA 00:44\n[download] 22.8% of 3.82MiB at 69.95KiB/s ETA 00:43\n[download] 24.7% of 3.82MiB at 69.37KiB/s ETA 00:42\n[download] 26.3% of 3.82MiB at 69.24KiB/s ETA 00:41\n[download] 28.0% of 3.82MiB at 69.47KiB/s ETA 00:40\n[download] 29.9% of 3.82MiB at 69.07KiB/s ETA 00:39\n[download] 31.5% of 3.82MiB at 69.07KiB/s ETA 00:38\n[download] 33.3% of 3.82MiB at 69.38KiB/s ETA 00:37\n[download] 35.2% of 3.82MiB at 69.21KiB/s ETA 00:36\n[download] 36.9% of 3.82MiB at 69.35KiB/s ETA 00:35\n[download] 38.7% of 3.82MiB at 69.73KiB/s ETA 00:34\n[download] 40.7% of 3.82MiB at 69.65KiB/s ETA 00:33\n[download] 42.5% of 3.82MiB at 69.82KiB/s ETA 00:32\n[download] 44.4% of 3.82MiB at 69.56KiB/s ETA 00:31\n[download] 46.0% of 3.82MiB at 69.57KiB/s ETA 00:30\n[download] 47.8% of 3.82MiB at 69.80KiB/s ETA 00:29\n[download] 49.8% of 3.82MiB at 69.65KiB/s ETA 00:28\n[download] 51.4% of 3.82MiB at 69.72KiB/s ETA 00:27\n[download] 53.3% of 3.82MiB at 69.48KiB/s ETA 00:26\n[download] 54.9% of 3.82MiB at 69.43KiB/s ETA 00:25\n[download] 56.6% of 3.82MiB at 69.56KiB/s ETA 00:24\n[download] 58.5% of 3.82MiB at 69.36KiB/s ETA 00:23\n[download] 60.2% of 3.82MiB at 69.37KiB/s ETA 00:22\n[download] 61.9% of 3.82MiB at 69.54KiB/s ETA 00:21\n[download] 63.9% of 3.82MiB at 69.42KiB/s ETA 00:20\n[download] 65.6% of 3.82MiB at 69.48KiB/s ETA 00:19\n[download] 67.4% of 3.82MiB at 69.68KiB/s ETA 00:18\n[download] 69.4% of 3.82MiB at 69.62KiB/s ETA 00:17\n[download] 71.1% of 3.82MiB at 69.71KiB/s ETA 00:16\n[download] 73.0% of 3.82MiB at 69.54KiB/s ETA 00:15\n[download] 74.6% of 3.82MiB at 69.53KiB/s ETA 00:14\n[download] 76.4% of 3.82MiB at 69.66KiB/s ETA 00:13\n[download] 78.3% of 3.82MiB at 69.58KiB/s ETA 00:12\n[download] 80.0% of 3.82MiB at 69.64KiB/s ETA 00:11\n[download] 81.9% of 3.82MiB at 69.44KiB/s ETA 00:10\n[download] 83.4% of 3.82MiB at 69.40KiB/s ETA 00:09\n[download] 85.2% of 3.82MiB at 69.48KiB/s ETA 00:08\n[download] 87.0% of 3.82MiB at 69.67KiB/s ETA 00:07\n[download] 89.1% of 3.82MiB at 69.66KiB/s ETA 00:06\n[download] 90.9% of 3.82MiB at 69.45KiB/s ETA 00:05\n[download] 92.4% of 3.82MiB at 69.69KiB/s ETA 00:04\n[download] 94.6% of 3.82MiB at 69.55KiB/s ETA 00:03\n[download] 96.3% of 3.82MiB at 69.56KiB/s ETA 00:02\n[download] 98.1% of 3.82MiB at 69.67KiB/s ETA 00:01\n[download] 100.0% of 3.82MiB at 69.70KiB/s ETA 00:00\n[download] 100% of 3.82MiB in 00:56\n[ffmpeg] Destination: /tmp/tmp5hp8fkyh/audio.wav\nDeleting original file /tmp/tmp5hp8fkyh/audio.webm (pass -k to keep)\nrunning the inference network...\n2022-03-16 13:55:58.101663: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\nplotting...\ndone!", "metrics": { "predict_time": 65.628347, "total_time": 99.547266 }, "output": "https://replicate.delivery/mgxm/ed180118-13c0-410b-bec1-478391f5bd67/out.png", "started_at": "2022-03-16T13:54:58.246225Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mnjyyydfrjdwjp7jtsfj2gnysm", "cancel": "https://api.replicate.com/v1/predictions/mnjyyydfrjdwjp7jtsfj2gnysm/cancel" }, "version": "3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb" }Generated in[youtube] CHekNnySAfM: Downloading webpage [youtube] CHekNnySAfM: Downloading player bd67d609 [download] Destination: /tmp/tmp5hp8fkyh/audio.webm [download] 0.0% of 3.82MiB at 7.33KiB/s ETA 08:53 [download] 0.1% of 3.82MiB at 21.97KiB/s ETA 02:57 [download] 0.2% of 3.82MiB at 51.24KiB/s ETA 01:16 [download] 0.4% of 3.82MiB at 109.68KiB/s ETA 00:35 [download] 0.8% of 3.82MiB at 88.27KiB/s ETA 00:43 [download] 1.6% of 3.82MiB at 76.81KiB/s ETA 00:50 [download] 3.2% of 3.82MiB at 73.03KiB/s ETA 00:51 [download] 5.0% of 3.82MiB at 68.01KiB/s ETA 00:54 [download] 6.6% of 3.82MiB at 67.48KiB/s ETA 00:54 [download] 8.3% of 3.82MiB at 68.29KiB/s ETA 00:52 [download] 10.1% of 3.82MiB at 69.88KiB/s ETA 00:50 [download] 12.1% of 3.82MiB at 69.50KiB/s ETA 00:49 [download] 13.8% of 3.82MiB at 70.00KiB/s ETA 00:48 [download] 15.7% of 3.82MiB at 69.33KiB/s ETA 00:47 [download] 17.3% of 3.82MiB at 69.45KiB/s ETA 00:46 [download] 19.2% of 3.82MiB at 70.08KiB/s ETA 00:45 [download] 21.1% of 3.82MiB at 69.75KiB/s ETA 00:44 [download] 22.8% of 3.82MiB at 69.95KiB/s ETA 00:43 [download] 24.7% of 3.82MiB at 69.37KiB/s ETA 00:42 [download] 26.3% of 3.82MiB at 69.24KiB/s ETA 00:41 [download] 28.0% of 3.82MiB at 69.47KiB/s ETA 00:40 [download] 29.9% of 3.82MiB at 69.07KiB/s ETA 00:39 [download] 31.5% of 3.82MiB at 69.07KiB/s ETA 00:38 [download] 33.3% of 3.82MiB at 69.38KiB/s ETA 00:37 [download] 35.2% of 3.82MiB at 69.21KiB/s ETA 00:36 [download] 36.9% of 3.82MiB at 69.35KiB/s ETA 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[download] 73.0% of 3.82MiB at 69.54KiB/s ETA 00:15 [download] 74.6% of 3.82MiB at 69.53KiB/s ETA 00:14 [download] 76.4% of 3.82MiB at 69.66KiB/s ETA 00:13 [download] 78.3% of 3.82MiB at 69.58KiB/s ETA 00:12 [download] 80.0% of 3.82MiB at 69.64KiB/s ETA 00:11 [download] 81.9% of 3.82MiB at 69.44KiB/s ETA 00:10 [download] 83.4% of 3.82MiB at 69.40KiB/s ETA 00:09 [download] 85.2% of 3.82MiB at 69.48KiB/s ETA 00:08 [download] 87.0% of 3.82MiB at 69.67KiB/s ETA 00:07 [download] 89.1% of 3.82MiB at 69.66KiB/s ETA 00:06 [download] 90.9% of 3.82MiB at 69.45KiB/s ETA 00:05 [download] 92.4% of 3.82MiB at 69.69KiB/s ETA 00:04 [download] 94.6% of 3.82MiB at 69.55KiB/s ETA 00:03 [download] 96.3% of 3.82MiB at 69.56KiB/s ETA 00:02 [download] 98.1% of 3.82MiB at 69.67KiB/s ETA 00:01 [download] 100.0% of 3.82MiB at 69.70KiB/s ETA 00:00 [download] 100% of 3.82MiB in 00:56 [ffmpeg] Destination: /tmp/tmp5hp8fkyh/audio.wav Deleting original file /tmp/tmp5hp8fkyh/audio.webm (pass -k to keep) running the inference network... 2022-03-16 13:55:58.101663: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz plotting... done!Prediction
mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabbIDnt7cptwdyvdzvi7x75tev55zyiStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- top_n
- "10"
- output_format
- Visualization
{ "audio": "https://replicate.delivery/mgxm/39dcbca1-bfe5-4058-be0d-2d88137c2b9d/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", { input: { audio: "https://replicate.delivery/mgxm/39dcbca1-bfe5-4058-be0d-2d88137c2b9d/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", input={ "audio": "https://replicate.delivery/mgxm/39dcbca1-bfe5-4058-be0d-2d88137c2b9d/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", "input": { "audio": "https://replicate.delivery/mgxm/39dcbca1-bfe5-4058-be0d-2d88137c2b9d/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-04-08T14:52:55.639944Z", "created_at": "2022-04-08T14:52:36.501715Z", "data_removed": false, "error": null, "id": "nt7cptwdyvdzvi7x75tev55zyi", "input": { "audio": "https://replicate.delivery/mgxm/39dcbca1-bfe5-4058-be0d-2d88137c2b9d/Muncho_Quixiera_Tener_Llevolul_Sumiciu.wav", "top_n": "10", "output_format": "Visualization" }, "logs": null, "metrics": { "predict_time": 12.658832, "total_time": 19.138229 }, "output": "https://replicate.delivery/mgxm/f027a38b-25e6-49f7-b5b7-f615113a13e9/out.png", "started_at": "2022-04-08T14:52:42.981112Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nt7cptwdyvdzvi7x75tev55zyi", "cancel": "https://api.replicate.com/v1/predictions/nt7cptwdyvdzvi7x75tev55zyi/cancel" }, "version": "3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb" }Generated inPrediction
mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabbIDgpf7sjan45emtbmqolpza4nk3qStatusSucceededSourceWebHardware–Total durationCreatedInput
- url
- https://www.youtube.com/watch?v=god7hAPv8f0
- top_n
- "10"
- output_format
- Visualization
{ "url": "https://www.youtube.com/watch?v=god7hAPv8f0", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", { input: { url: "https://www.youtube.com/watch?v=god7hAPv8f0", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", input={ "url": "https://www.youtube.com/watch?v=god7hAPv8f0", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb", "input": { "url": "https://www.youtube.com/watch?v=god7hAPv8f0", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-03-16T10:55:38.809372Z", "created_at": "2022-03-16T10:53:56.477939Z", "data_removed": false, "error": null, "id": "gpf7sjan45emtbmqolpza4nk3q", "input": { "url": "https://www.youtube.com/watch?v=god7hAPv8f0", "top_n": "10", "output_format": "Visualization" }, "logs": "[youtube] god7hAPv8f0: Downloading webpage\n[youtube] god7hAPv8f0: Downloading player bd67d609\n[download] Destination: /tmp/tmpyz4ovlhn/audio.webm\n\n[download] 0.0% of 4.61MiB at 5.83KiB/s ETA 13:30\n[download] 0.1% of 4.61MiB at 17.46KiB/s ETA 04:30\n[download] 0.1% of 4.61MiB at 40.73KiB/s ETA 01:55\n[download] 0.3% of 4.61MiB at 87.22KiB/s ETA 00:53\n[download] 0.7% of 4.61MiB at 70.20KiB/s ETA 01:06\n[download] 1.3% of 4.61MiB at 61.10KiB/s ETA 01:16\n[download] 2.5% of 4.61MiB at 53.67KiB/s ETA 01:25\n[download] 3.5% of 4.61MiB at 53.96KiB/s ETA 01:24\n[download] 4.6% of 4.61MiB at 56.09KiB/s ETA 01:20\n[download] 6.0% of 4.61MiB at 55.88KiB/s ETA 01:19\n[download] 7.2% of 4.61MiB at 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00:22\n[download] 74.8% of 4.61MiB at 55.42KiB/s ETA 00:21\n[download] 76.1% of 4.61MiB at 55.36KiB/s ETA 00:20\n[download] 77.2% of 4.61MiB at 55.43KiB/s ETA 00:19\n[download] 78.5% of 4.61MiB at 55.39KiB/s ETA 00:18\n[download] 79.6% of 4.61MiB at 55.44KiB/s ETA 00:17\n[download] 80.9% of 4.61MiB at 55.38KiB/s ETA 00:16\n[download] 82.0% of 4.61MiB at 55.43KiB/s ETA 00:15\n[download] 83.2% of 4.61MiB at 55.38KiB/s ETA 00:14\n[download] 84.3% of 4.61MiB at 55.44KiB/s ETA 00:13\n[download] 85.6% of 4.61MiB at 55.39KiB/s ETA 00:12\n[download] 86.7% of 4.61MiB at 55.45KiB/s ETA 00:11\n[download] 88.0% of 4.61MiB at 55.40KiB/s ETA 00:10\n[download] 89.1% of 4.61MiB at 55.24KiB/s ETA 00:09\n[download] 90.1% of 4.61MiB at 55.40KiB/s ETA 00:08\n[download] 91.7% of 4.61MiB at 55.35KiB/s ETA 00:07\n[download] 92.8% of 4.61MiB at 55.41KiB/s ETA 00:06\n[download] 94.1% of 4.61MiB at 55.37KiB/s ETA 00:05\n[download] 95.2% of 4.61MiB at 55.44KiB/s ETA 00:04\n[download] 96.5% of 4.61MiB at 55.41KiB/s ETA 00:02\n[download] 97.6% of 4.61MiB at 55.29KiB/s ETA 00:02\n[download] 98.6% of 4.61MiB at 55.25KiB/s ETA 00:01\n[download] 99.7% of 4.61MiB at 55.31KiB/s ETA 00:00\n[download] 100.0% of 4.61MiB at 55.43KiB/s ETA 00:00\n[download] 100% of 4.61MiB in 01:25\n[ffmpeg] Destination: /tmp/tmpyz4ovlhn/audio.wav\nDeleting original file /tmp/tmpyz4ovlhn/audio.webm (pass -k to keep)\nrunning the inference network...\n2022-03-16 10:55:32.342049: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz\nplotting...\ndone!", "metrics": { "predict_time": 95.33379, "total_time": 102.331433 }, "output": "https://replicate.delivery/mgxm/187f8ae3-f79d-405a-b989-999fcc50715f/out.png", "started_at": "2022-03-16T10:54:03.475582Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gpf7sjan45emtbmqolpza4nk3q", "cancel": "https://api.replicate.com/v1/predictions/gpf7sjan45emtbmqolpza4nk3q/cancel" }, "version": "3b1d08bbeea1030fa31a71eef8e9440857cd3b3c780fd928b4d3068366d3cabb" }Generated in[youtube] god7hAPv8f0: Downloading webpage [youtube] god7hAPv8f0: Downloading player bd67d609 [download] Destination: /tmp/tmpyz4ovlhn/audio.webm [download] 0.0% of 4.61MiB at 5.83KiB/s ETA 13:30 [download] 0.1% of 4.61MiB at 17.46KiB/s ETA 04:30 [download] 0.1% of 4.61MiB at 40.73KiB/s ETA 01:55 [download] 0.3% of 4.61MiB at 87.22KiB/s ETA 00:53 [download] 0.7% of 4.61MiB at 70.20KiB/s ETA 01:06 [download] 1.3% of 4.61MiB at 61.10KiB/s ETA 01:16 [download] 2.5% of 4.61MiB at 53.67KiB/s ETA 01:25 [download] 3.5% of 4.61MiB at 53.96KiB/s ETA 01:24 [download] 4.6% of 4.61MiB at 56.09KiB/s ETA 01:20 [download] 6.0% of 4.61MiB at 55.88KiB/s ETA 01:19 [download] 7.2% of 4.61MiB at 54.16KiB/s ETA 01:20 [download] 8.1% of 4.61MiB at 54.19KiB/s ETA 01:20 [download] 9.3% of 4.61MiB at 55.17KiB/s ETA 01:17 [download] 10.6% of 4.61MiB at 55.00KiB/s ETA 01:16 [download] 11.8% of 4.61MiB at 55.65KiB/s ETA 01:14 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original file /tmp/tmpyz4ovlhn/audio.webm (pass -k to keep) running the inference network... 2022-03-16 10:55:32.342049: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2299995000 Hz plotting... done!Prediction
mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0bIDt26f4f7ilna4pe3zluga2xrpv4StatusSucceededSourceWebHardware–Total durationCreatedInput
- url
- https://www.youtube.com/watch?v=CHekNnySAfM
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- top_n
- "10"
- output_format
- Visualization
{ "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "audio": "https://replicate.delivery/mgxm/398d654a-ce4c-4bad-8058-66cfe5c680fd/Earth_Wind__Fire_-_Boogie_Wonderland_Official_Video-god7hA.opus", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", { input: { url: "https://www.youtube.com/watch?v=CHekNnySAfM", audio: "https://replicate.delivery/mgxm/398d654a-ce4c-4bad-8058-66cfe5c680fd/Earth_Wind__Fire_-_Boogie_Wonderland_Official_Video-god7hA.opus", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", input={ "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "audio": "https://replicate.delivery/mgxm/398d654a-ce4c-4bad-8058-66cfe5c680fd/Earth_Wind__Fire_-_Boogie_Wonderland_Official_Video-god7hA.opus", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", "input": { "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "audio": "https://replicate.delivery/mgxm/398d654a-ce4c-4bad-8058-66cfe5c680fd/Earth_Wind__Fire_-_Boogie_Wonderland_Official_Video-god7hA.opus", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-06-13T13:12:52.046876Z", "created_at": "2022-06-13T13:11:41.463735Z", "data_removed": false, "error": null, "id": "t26f4f7ilna4pe3zluga2xrpv4", "input": { "url": "https://www.youtube.com/watch?v=CHekNnySAfM", "audio": "https://replicate.delivery/mgxm/398d654a-ce4c-4bad-8058-66cfe5c680fd/Earth_Wind__Fire_-_Boogie_Wonderland_Official_Video-god7hA.opus", "top_n": "10", "output_format": "Visualization" }, "logs": null, "metrics": { "predict_time": 60.750285, "total_time": 70.583141 }, "output": "https://replicate.delivery/mgxm/30b16919-535d-418e-80ce-e646521e2c25/out.png", "started_at": "2022-06-13T13:11:51.296591Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/t26f4f7ilna4pe3zluga2xrpv4", "cancel": "https://api.replicate.com/v1/predictions/t26f4f7ilna4pe3zluga2xrpv4/cancel" }, "version": "cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b" }Generated inPrediction
mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0bID3gg4dgjx6vbchm6wc2d72urq6aStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- top_n
- "10"
- output_format
- Visualization
{ "audio": "https://replicate.delivery/mgxm/269e0898-4185-4dc1-b472-6eab1efb49e9/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", { input: { audio: "https://replicate.delivery/mgxm/269e0898-4185-4dc1-b472-6eab1efb49e9/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", input={ "audio": "https://replicate.delivery/mgxm/269e0898-4185-4dc1-b472-6eab1efb49e9/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", "input": { "audio": "https://replicate.delivery/mgxm/269e0898-4185-4dc1-b472-6eab1efb49e9/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-06-13T13:14:29.205819Z", "created_at": "2022-06-13T13:14:16.117687Z", "data_removed": false, "error": null, "id": "3gg4dgjx6vbchm6wc2d72urq6a", "input": { "audio": "https://replicate.delivery/mgxm/269e0898-4185-4dc1-b472-6eab1efb49e9/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" }, "logs": null, "metrics": { "predict_time": 12.94615, "total_time": 13.088132 }, "output": "https://replicate.delivery/mgxm/404c9df5-83d7-4ef7-9cc3-d8e6505b423e/out.png", "started_at": "2022-06-13T13:14:16.259669Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3gg4dgjx6vbchm6wc2d72urq6a", "cancel": "https://api.replicate.com/v1/predictions/3gg4dgjx6vbchm6wc2d72urq6a/cancel" }, "version": "cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b" }Generated inPrediction
mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0bIDsj5srj2t25hmxd7yajhurw5slyStatusSucceededSourceWebHardware–Total durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- top_n
- "10"
- output_format
- Visualization
{ "audio": "https://replicate.delivery/mgxm/fa11978f-e39e-4209-8569-3935499dc36a/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", { input: { audio: "https://replicate.delivery/mgxm/fa11978f-e39e-4209-8569-3935499dc36a/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", top_n: "10", output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", input={ "audio": "https://replicate.delivery/mgxm/fa11978f-e39e-4209-8569-3935499dc36a/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b", "input": { "audio": "https://replicate.delivery/mgxm/fa11978f-e39e-4209-8569-3935499dc36a/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-06-13T13:15:25.170525Z", "created_at": "2022-06-13T13:15:12.643257Z", "data_removed": false, "error": null, "id": "sj5srj2t25hmxd7yajhurw5sly", "input": { "audio": "https://replicate.delivery/mgxm/fa11978f-e39e-4209-8569-3935499dc36a/Bob_Marley_-_Is_This_Love-CHekNnySAfM.mp3", "top_n": "10", "output_format": "Visualization" }, "logs": null, "metrics": { "predict_time": 12.362656, "total_time": 12.527268 }, "output": "https://replicate.delivery/mgxm/cd0f032d-ae7e-4169-99c8-017eddbe6c59/out.png", "started_at": "2022-06-13T13:15:12.807869Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/sj5srj2t25hmxd7yajhurw5sly", "cancel": "https://api.replicate.com/v1/predictions/sj5srj2t25hmxd7yajhurw5sly/cancel" }, "version": "cf730ddb17b45f8ab6c0499f077a0e076cc0c08ac14df8ba79017b2f94e56e0b" }Generated inPrediction
mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1ID6ezfc6jbqbvxgpthemimw57aemStatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- top_n
- 10
- output_format
- Visualization
{ "audio": "https://replicate.delivery/pbxt/JosNr6W7Id9w7wm461qmmvZlaEyvtVEmWIyhYxDooJi2xmPW/07%20-%20The%20Enemy.mp3", "top_n": 10, "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1", { input: { audio: "https://replicate.delivery/pbxt/JosNr6W7Id9w7wm461qmmvZlaEyvtVEmWIyhYxDooJi2xmPW/07%20-%20The%20Enemy.mp3", top_n: 10, output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1", input={ "audio": "https://replicate.delivery/pbxt/JosNr6W7Id9w7wm461qmmvZlaEyvtVEmWIyhYxDooJi2xmPW/07%20-%20The%20Enemy.mp3", "top_n": 10, "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1", "input": { "audio": "https://replicate.delivery/pbxt/JosNr6W7Id9w7wm461qmmvZlaEyvtVEmWIyhYxDooJi2xmPW/07%20-%20The%20Enemy.mp3", "top_n": 10, "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-04T18:08:03.282238Z", "created_at": "2023-11-04T18:07:58.146409Z", "data_removed": false, "error": null, "id": "6ezfc6jbqbvxgpthemimw57aem", "input": { "audio": "https://replicate.delivery/pbxt/JosNr6W7Id9w7wm461qmmvZlaEyvtVEmWIyhYxDooJi2xmPW/07%20-%20The%20Enemy.mp3", "top_n": 10, "output_format": "Visualization" }, "logs": "loading audio...\nrunning the model...\nplotting...\ndone!", "metrics": { "predict_time": 5.181851, "total_time": 5.135829 }, "output": "https://replicate.delivery/pbxt/QFeeTEFF3gjDOEOXJz6SyMWCNvvLZvf4CZ4qVQAWRJsHUHqjA/out.png", "started_at": "2023-11-04T18:07:58.100387Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6ezfc6jbqbvxgpthemimw57aem", "cancel": "https://api.replicate.com/v1/predictions/6ezfc6jbqbvxgpthemimw57aem/cancel" }, "version": "1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1" }Generated inloading audio... running the model... plotting... done!Prediction
mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1ID567nd2bb7mr7fkuspjpva3ia5yStatusSucceededSourceWebHardwareCPUTotal durationCreatedInput
- audio
- Video Player is loading.Current Time 00:00:000/Duration 00:00:000Loaded: 0%Stream Type LIVERemaining Time -00:00:0001x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
- top_n
- 10
- output_format
- Visualization
{ "audio": "https://replicate.delivery/pbxt/JosPRo7HlmW5dFGZko5EIFkKaHnkPxEQRrjCcM4SLtkfuscc/02%20-%20Exprimelimones%20%28Buleri%CC%81as%29.flac", "top_n": 10, "output_format": "Visualization" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1", { input: { audio: "https://replicate.delivery/pbxt/JosPRo7HlmW5dFGZko5EIFkKaHnkPxEQRrjCcM4SLtkfuscc/02%20-%20Exprimelimones%20%28Buleri%CC%81as%29.flac", top_n: 10, output_format: "Visualization" } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1", input={ "audio": "https://replicate.delivery/pbxt/JosPRo7HlmW5dFGZko5EIFkKaHnkPxEQRrjCcM4SLtkfuscc/02%20-%20Exprimelimones%20%28Buleri%CC%81as%29.flac", "top_n": 10, "output_format": "Visualization" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mtg/effnet-discogs using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "mtg/effnet-discogs:1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1", "input": { "audio": "https://replicate.delivery/pbxt/JosPRo7HlmW5dFGZko5EIFkKaHnkPxEQRrjCcM4SLtkfuscc/02%20-%20Exprimelimones%20%28Buleri%CC%81as%29.flac", "top_n": 10, "output_format": "Visualization" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-04T18:09:47.024918Z", "created_at": "2023-11-04T18:09:41.315447Z", "data_removed": false, "error": null, "id": "567nd2bb7mr7fkuspjpva3ia5y", "input": { "audio": "https://replicate.delivery/pbxt/JosPRo7HlmW5dFGZko5EIFkKaHnkPxEQRrjCcM4SLtkfuscc/02%20-%20Exprimelimones%20%28Buleri%CC%81as%29.flac", "top_n": 10, "output_format": "Visualization" }, "logs": "loading audio...\nrunning the model...\nplotting...\ndone!", "metrics": { "predict_time": 5.74006, "total_time": 5.709471 }, "output": "https://replicate.delivery/pbxt/6Nc3z6cvRSJqLB9pX0Ynn2deSDMSexKgrt22TycvDmbqrD1RA/out.png", "started_at": "2023-11-04T18:09:41.284858Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/567nd2bb7mr7fkuspjpva3ia5y", "cancel": "https://api.replicate.com/v1/predictions/567nd2bb7mr7fkuspjpva3ia5y/cancel" }, "version": "1532dd069fb4f0e27c6833e28815f6b8c194dfec76fd9cd73460540fd720ffe1" }Generated inloading audio... running the model... plotting... done!
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