thudm
/
cogvideox-i2v
Image-to-Video Diffusion Models with An Expert Transformer
Prediction
thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58IDqb7hex84wsrgj0cj2nj95qk4y4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- image
- prompt
- Starry sky slowly rotating.
- num_frames
- 49
- guidance_scale
- 6
- num_inference_steps
- 50
{ "image": "https://replicate.delivery/pbxt/Lf97CMO0Sz0sZ0IuQarZRT8TbcMz4pCurtiLSKWDBPSTMb1S/input.jpg", "prompt": "Starry sky slowly rotating.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 50 }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 thudm/cogvideox-i2v using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58", { input: { image: "https://replicate.delivery/pbxt/Lf97CMO0Sz0sZ0IuQarZRT8TbcMz4pCurtiLSKWDBPSTMb1S/input.jpg", prompt: "Starry sky slowly rotating.", num_frames: 49, guidance_scale: 6, num_inference_steps: 50 } } ); // 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 thudm/cogvideox-i2v using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58", input={ "image": "https://replicate.delivery/pbxt/Lf97CMO0Sz0sZ0IuQarZRT8TbcMz4pCurtiLSKWDBPSTMb1S/input.jpg", "prompt": "Starry sky slowly rotating.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run thudm/cogvideox-i2v 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": "thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58", "input": { "image": "https://replicate.delivery/pbxt/Lf97CMO0Sz0sZ0IuQarZRT8TbcMz4pCurtiLSKWDBPSTMb1S/input.jpg", "prompt": "Starry sky slowly rotating.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-21T16:31:24.720449Z", "created_at": "2024-09-21T16:22:09.382000Z", "data_removed": false, "error": null, "id": "qb7hex84wsrgj0cj2nj95qk4y4", "input": { "image": "https://replicate.delivery/pbxt/Lf97CMO0Sz0sZ0IuQarZRT8TbcMz4pCurtiLSKWDBPSTMb1S/input.jpg", "prompt": "Starry sky slowly rotating.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 50 }, "logs": "Using seed: 10643\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:12<10:16, 12.59s/it]\n 4%|▍ | 2/50 [00:20<07:41, 9.62s/it]\n 6%|▌ | 3/50 [00:27<06:47, 8.66s/it]\n 8%|▊ | 4/50 [00:35<06:18, 8.22s/it]\n 10%|█ | 5/50 [00:42<05:59, 7.99s/it]\n 12%|█▏ | 6/50 [00:50<05:45, 7.85s/it]\n 14%|█▍ | 7/50 [00:57<05:34, 7.77s/it]\n 16%|█▌ | 8/50 [01:05<05:24, 7.72s/it]\n 18%|█▊ | 9/50 [01:13<05:14, 7.68s/it]\n 20%|██ | 10/50 [01:20<05:06, 7.65s/it]\n 22%|██▏ | 11/50 [01:28<04:57, 7.64s/it]\n 24%|██▍ | 12/50 [01:35<04:49, 7.63s/it]\n 26%|██▌ | 13/50 [01:43<04:42, 7.62s/it]\n 28%|██▊ | 14/50 [01:51<04:34, 7.62s/it]\n 30%|███ | 15/50 [01:58<04:26, 7.62s/it]\n 32%|███▏ | 16/50 [02:06<04:19, 7.63s/it]\n 34%|███▍ | 17/50 [02:14<04:11, 7.63s/it]\n 36%|███▌ | 18/50 [02:21<04:04, 7.63s/it]\n 38%|███▊ | 19/50 [02:29<03:56, 7.63s/it]\n 40%|████ | 20/50 [02:37<03:49, 7.63s/it]\n 42%|████▏ | 21/50 [02:44<03:41, 7.63s/it]\n 44%|████▍ | 22/50 [02:52<03:33, 7.64s/it]\n 46%|████▌ | 23/50 [02:59<03:26, 7.64s/it]\n 48%|████▊ | 24/50 [03:07<03:18, 7.64s/it]\n 50%|█████ | 25/50 [03:15<03:10, 7.64s/it]\n 52%|█████▏ | 26/50 [03:22<03:03, 7.64s/it]\n 54%|█████▍ | 27/50 [03:30<02:55, 7.64s/it]\n 56%|█████▌ | 28/50 [03:38<02:48, 7.64s/it]\n 58%|█████▊ | 29/50 [03:45<02:40, 7.64s/it]\n 60%|██████ | 30/50 [03:53<02:32, 7.64s/it]\n 62%|██████▏ | 31/50 [04:01<02:25, 7.65s/it]\n 64%|██████▍ | 32/50 [04:08<02:17, 7.65s/it]\n 66%|██████▌ | 33/50 [04:16<02:10, 7.66s/it]\n 68%|██████▊ | 34/50 [04:24<02:02, 7.66s/it]\n 70%|███████ | 35/50 [04:31<01:54, 7.66s/it]\n 72%|███████▏ | 36/50 [04:39<01:47, 7.66s/it]\n 74%|███████▍ | 37/50 [04:47<01:39, 7.66s/it]\n 76%|███████▌ | 38/50 [04:54<01:31, 7.66s/it]\n 78%|███████▊ | 39/50 [05:02<01:24, 7.66s/it]\n 80%|████████ | 40/50 [05:10<01:16, 7.66s/it]\n 82%|████████▏ | 41/50 [05:17<01:08, 7.66s/it]\n 84%|████████▍ | 42/50 [05:25<01:01, 7.66s/it]\n 86%|████████▌ | 43/50 [05:32<00:53, 7.66s/it]\n 88%|████████▊ | 44/50 [05:40<00:45, 7.66s/it]\n 90%|█████████ | 45/50 [05:48<00:38, 7.66s/it]\n 92%|█████████▏| 46/50 [05:55<00:30, 7.66s/it]\n 94%|█████████▍| 47/50 [06:03<00:22, 7.66s/it]\n 96%|█████████▌| 48/50 [06:11<00:15, 7.66s/it]\n 98%|█████████▊| 49/50 [06:18<00:07, 7.66s/it]\n100%|██████████| 50/50 [06:26<00:00, 7.66s/it]\n100%|██████████| 50/50 [06:26<00:00, 7.73s/it]", "metrics": { "predict_time": 406.217533968, "total_time": 555.338449 }, "output": "https://replicate.delivery/pbxt/ru4kvN7GrOIlNVQGin3bYZsKYsacFmIqZty4tfEusqmtNlvJA/out.mp4", "started_at": "2024-09-21T16:24:38.502915Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/qb7hex84wsrgj0cj2nj95qk4y4", "cancel": "https://api.replicate.com/v1/predictions/qb7hex84wsrgj0cj2nj95qk4y4/cancel" }, "version": "82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58" }Generated inUsing seed: 10643 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:12<10:16, 12.59s/it] 4%|▍ | 2/50 [00:20<07:41, 9.62s/it] 6%|▌ | 3/50 [00:27<06:47, 8.66s/it] 8%|▊ | 4/50 [00:35<06:18, 8.22s/it] 10%|█ | 5/50 [00:42<05:59, 7.99s/it] 12%|█▏ | 6/50 [00:50<05:45, 7.85s/it] 14%|█▍ | 7/50 [00:57<05:34, 7.77s/it] 16%|█▌ | 8/50 [01:05<05:24, 7.72s/it] 18%|█▊ | 9/50 [01:13<05:14, 7.68s/it] 20%|██ | 10/50 [01:20<05:06, 7.65s/it] 22%|██▏ | 11/50 [01:28<04:57, 7.64s/it] 24%|██▍ | 12/50 [01:35<04:49, 7.63s/it] 26%|██▌ | 13/50 [01:43<04:42, 7.62s/it] 28%|██▊ | 14/50 [01:51<04:34, 7.62s/it] 30%|███ | 15/50 [01:58<04:26, 7.62s/it] 32%|███▏ | 16/50 [02:06<04:19, 7.63s/it] 34%|███▍ | 17/50 [02:14<04:11, 7.63s/it] 36%|███▌ | 18/50 [02:21<04:04, 7.63s/it] 38%|███▊ | 19/50 [02:29<03:56, 7.63s/it] 40%|████ | 20/50 [02:37<03:49, 7.63s/it] 42%|████▏ | 21/50 [02:44<03:41, 7.63s/it] 44%|████▍ | 22/50 [02:52<03:33, 7.64s/it] 46%|████▌ | 23/50 [02:59<03:26, 7.64s/it] 48%|████▊ | 24/50 [03:07<03:18, 7.64s/it] 50%|█████ | 25/50 [03:15<03:10, 7.64s/it] 52%|█████▏ | 26/50 [03:22<03:03, 7.64s/it] 54%|█████▍ | 27/50 [03:30<02:55, 7.64s/it] 56%|█████▌ | 28/50 [03:38<02:48, 7.64s/it] 58%|█████▊ | 29/50 [03:45<02:40, 7.64s/it] 60%|██████ | 30/50 [03:53<02:32, 7.64s/it] 62%|██████▏ | 31/50 [04:01<02:25, 7.65s/it] 64%|██████▍ | 32/50 [04:08<02:17, 7.65s/it] 66%|██████▌ | 33/50 [04:16<02:10, 7.66s/it] 68%|██████▊ | 34/50 [04:24<02:02, 7.66s/it] 70%|███████ | 35/50 [04:31<01:54, 7.66s/it] 72%|███████▏ | 36/50 [04:39<01:47, 7.66s/it] 74%|███████▍ | 37/50 [04:47<01:39, 7.66s/it] 76%|███████▌ | 38/50 [04:54<01:31, 7.66s/it] 78%|███████▊ | 39/50 [05:02<01:24, 7.66s/it] 80%|████████ | 40/50 [05:10<01:16, 7.66s/it] 82%|████████▏ | 41/50 [05:17<01:08, 7.66s/it] 84%|████████▍ | 42/50 [05:25<01:01, 7.66s/it] 86%|████████▌ | 43/50 [05:32<00:53, 7.66s/it] 88%|████████▊ | 44/50 [05:40<00:45, 7.66s/it] 90%|█████████ | 45/50 [05:48<00:38, 7.66s/it] 92%|█████████▏| 46/50 [05:55<00:30, 7.66s/it] 94%|█████████▍| 47/50 [06:03<00:22, 7.66s/it] 96%|█████████▌| 48/50 [06:11<00:15, 7.66s/it] 98%|█████████▊| 49/50 [06:18<00:07, 7.66s/it] 100%|██████████| 50/50 [06:26<00:00, 7.66s/it] 100%|██████████| 50/50 [06:26<00:00, 7.73s/it]Prediction
thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58ID3twjpr3mg5rgj0cj2npvkpcyr8StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @chenxwhInput
- image
- prompt
- A woman is riding a bicycle at high speed. Focused, detailed, realistic.
- num_frames
- 49
- guidance_scale
- 6
- num_inference_steps
- 70
{ "image": "https://replicate.delivery/pbxt/Lf9Gx3mUUFQKLpL3TiddzCygMzHFqrKYdEIu9vg1wealzvzy/Liv-EnviLiv-4-280dc65.jpg", "prompt": "A woman is riding a bicycle at high speed. Focused, detailed, realistic.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 70 }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 thudm/cogvideox-i2v using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58", { input: { image: "https://replicate.delivery/pbxt/Lf9Gx3mUUFQKLpL3TiddzCygMzHFqrKYdEIu9vg1wealzvzy/Liv-EnviLiv-4-280dc65.jpg", prompt: "A woman is riding a bicycle at high speed. Focused, detailed, realistic.", num_frames: 49, guidance_scale: 6, num_inference_steps: 70 } } ); // 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 thudm/cogvideox-i2v using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58", input={ "image": "https://replicate.delivery/pbxt/Lf9Gx3mUUFQKLpL3TiddzCygMzHFqrKYdEIu9vg1wealzvzy/Liv-EnviLiv-4-280dc65.jpg", "prompt": "A woman is riding a bicycle at high speed. Focused, detailed, realistic.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 70 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run thudm/cogvideox-i2v 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": "thudm/cogvideox-i2v:82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58", "input": { "image": "https://replicate.delivery/pbxt/Lf9Gx3mUUFQKLpL3TiddzCygMzHFqrKYdEIu9vg1wealzvzy/Liv-EnviLiv-4-280dc65.jpg", "prompt": "A woman is riding a bicycle at high speed. Focused, detailed, realistic.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 70 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-21T16:41:47.598866Z", "created_at": "2024-09-21T16:32:27.777000Z", "data_removed": false, "error": null, "id": "3twjpr3mg5rgj0cj2npvkpcyr8", "input": { "image": "https://replicate.delivery/pbxt/Lf9Gx3mUUFQKLpL3TiddzCygMzHFqrKYdEIu9vg1wealzvzy/Liv-EnviLiv-4-280dc65.jpg", "prompt": "A woman is riding a bicycle at high speed. Focused, detailed, realistic.", "num_frames": 49, "guidance_scale": 6, "num_inference_steps": 70 }, "logs": "Using seed: 58939\n 0%| | 0/70 [00:00<?, ?it/s]\n 1%|▏ | 1/70 [00:14<16:35, 14.42s/it]\n 3%|▎ | 2/70 [00:21<11:43, 10.35s/it]\n 4%|▍ | 3/70 [00:29<10:06, 9.06s/it]\n 6%|▌ | 4/70 [00:36<09:18, 8.46s/it]\n 7%|▋ | 5/70 [00:44<08:48, 8.14s/it]\n 9%|▊ | 6/70 [00:52<08:28, 7.95s/it]\n 10%|█ | 7/70 [00:59<08:13, 7.83s/it]\n 11%|█▏ | 8/70 [01:07<08:00, 7.75s/it]\n 13%|█▎ | 9/70 [01:14<07:49, 7.70s/it]\n 14%|█▍ | 10/70 [01:22<07:39, 7.67s/it]\n 16%|█▌ | 11/70 [01:30<07:30, 7.64s/it]\n 17%|█▋ | 12/70 [01:37<07:21, 7.62s/it]\n 19%|█▊ | 13/70 [01:45<07:13, 7.61s/it]\n 20%|██ | 14/70 [01:52<07:05, 7.60s/it]\n 21%|██▏ | 15/70 [02:00<06:57, 7.60s/it]\n 23%|██▎ | 16/70 [02:07<06:50, 7.59s/it]\n 24%|██▍ | 17/70 [02:15<06:42, 7.59s/it]\n 26%|██▌ | 18/70 [02:23<06:35, 7.60s/it]\n 27%|██▋ | 19/70 [02:30<06:27, 7.60s/it]\n 29%|██▊ | 20/70 [02:38<06:19, 7.60s/it]\n 30%|███ | 21/70 [02:45<06:12, 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[08:20<00:37, 7.60s/it]\n 94%|█████████▍| 66/70 [08:28<00:30, 7.60s/it]\n 96%|█████████▌| 67/70 [08:35<00:22, 7.60s/it]\n 97%|█████████▋| 68/70 [08:43<00:15, 7.60s/it]\n 99%|█████████▊| 69/70 [08:50<00:07, 7.60s/it]\n100%|██████████| 70/70 [08:58<00:00, 7.60s/it]\n100%|██████████| 70/70 [08:58<00:00, 7.69s/it]", "metrics": { "predict_time": 559.722271425, "total_time": 559.821866 }, "output": "https://replicate.delivery/pbxt/E1a1OQSKY1L8NVcC6xgA66DlB6zfKwqekdf72AAsQDKVKVeNB/out.mp4", "started_at": "2024-09-21T16:32:27.876595Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3twjpr3mg5rgj0cj2npvkpcyr8", "cancel": "https://api.replicate.com/v1/predictions/3twjpr3mg5rgj0cj2npvkpcyr8/cancel" }, "version": "82caaa79520e03b3963c975e38dd68ac8a6b18a8a39c19fd8dc03b4ed4b91c58" }Generated inUsing seed: 58939 0%| | 0/70 [00:00<?, ?it/s] 1%|▏ | 1/70 [00:14<16:35, 14.42s/it] 3%|▎ | 2/70 [00:21<11:43, 10.35s/it] 4%|▍ | 3/70 [00:29<10:06, 9.06s/it] 6%|▌ | 4/70 [00:36<09:18, 8.46s/it] 7%|▋ | 5/70 [00:44<08:48, 8.14s/it] 9%|▊ | 6/70 [00:52<08:28, 7.95s/it] 10%|█ | 7/70 [00:59<08:13, 7.83s/it] 11%|█▏ | 8/70 [01:07<08:00, 7.75s/it] 13%|█▎ | 9/70 [01:14<07:49, 7.70s/it] 14%|█▍ | 10/70 [01:22<07:39, 7.67s/it] 16%|█▌ | 11/70 [01:30<07:30, 7.64s/it] 17%|█▋ | 12/70 [01:37<07:21, 7.62s/it] 19%|█▊ | 13/70 [01:45<07:13, 7.61s/it] 20%|██ | 14/70 [01:52<07:05, 7.60s/it] 21%|██▏ | 15/70 [02:00<06:57, 7.60s/it] 23%|██▎ | 16/70 [02:07<06:50, 7.59s/it] 24%|██▍ | 17/70 [02:15<06:42, 7.59s/it] 26%|██▌ | 18/70 [02:23<06:35, 7.60s/it] 27%|██▋ | 19/70 [02:30<06:27, 7.60s/it] 29%|██▊ | 20/70 [02:38<06:19, 7.60s/it] 30%|███ | 21/70 [02:45<06:12, 7.60s/it] 31%|███▏ | 22/70 [02:53<06:04, 7.60s/it] 33%|███▎ | 23/70 [03:01<05:57, 7.60s/it] 34%|███▍ | 24/70 [03:08<05:49, 7.60s/it] 36%|███▌ | 25/70 [03:16<05:41, 7.60s/it] 37%|███▋ | 26/70 [03:23<05:34, 7.60s/it] 39%|███▊ | 27/70 [03:31<05:26, 7.60s/it] 40%|████ | 28/70 [03:39<05:19, 7.60s/it] 41%|████▏ | 29/70 [03:46<05:11, 7.60s/it] 43%|████▎ | 30/70 [03:54<05:03, 7.60s/it] 44%|████▍ | 31/70 [04:01<04:56, 7.60s/it] 46%|████▌ | 32/70 [04:09<04:48, 7.60s/it] 47%|████▋ | 33/70 [04:17<04:41, 7.60s/it] 49%|████▊ | 34/70 [04:24<04:33, 7.60s/it] 50%|█████ | 35/70 [04:32<04:25, 7.60s/it] 51%|█████▏ | 36/70 [04:39<04:18, 7.60s/it] 53%|█████▎ | 37/70 [04:47<04:10, 7.60s/it] 54%|█████▍ | 38/70 [04:55<04:03, 7.60s/it] 56%|█████▌ | 39/70 [05:02<03:55, 7.60s/it] 57%|█████▋ | 40/70 [05:10<03:47, 7.60s/it] 59%|█████▊ | 41/70 [05:17<03:40, 7.60s/it] 60%|██████ | 42/70 [05:25<03:32, 7.60s/it] 61%|██████▏ | 43/70 [05:33<03:25, 7.60s/it] 63%|██████▎ | 44/70 [05:40<03:17, 7.60s/it] 64%|██████▍ | 45/70 [05:48<03:09, 7.60s/it] 66%|██████▌ | 46/70 [05:56<03:04, 7.68s/it] 67%|██████▋ | 47/70 [06:03<02:56, 7.66s/it] 69%|██████▊ | 48/70 [06:11<02:48, 7.64s/it] 70%|███████ | 49/70 [06:18<02:40, 7.63s/it] 71%|███████▏ | 50/70 [06:26<02:32, 7.62s/it] 73%|███████▎ | 51/70 [06:34<02:24, 7.61s/it] 74%|███████▍ | 52/70 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