pollinations
/
3d-photo-inpainting
3D Photography using Context-aware Layered Depth Inpainting
Prediction
pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9deIDmbell7jvjvav5etay3cqljruaaStatusSucceededSourceWebHardware–Total durationCreatedInput
- image
{ "image": "https://replicate.delivery/pbxt/II7KEI8StSKyHAJdABnGOzS7RXsgRMl2jL6ewsPe6rxEedKh/out-2%20%282%29.png" }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 pollinations/3d-photo-inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de", { input: { image: "https://replicate.delivery/pbxt/II7KEI8StSKyHAJdABnGOzS7RXsgRMl2jL6ewsPe6rxEedKh/out-2%20%282%29.png" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);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 pollinations/3d-photo-inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de", input={ "image": "https://replicate.delivery/pbxt/II7KEI8StSKyHAJdABnGOzS7RXsgRMl2jL6ewsPe6rxEedKh/out-2%20%282%29.png" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run pollinations/3d-photo-inpainting 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": "pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de", "input": { "image": "https://replicate.delivery/pbxt/II7KEI8StSKyHAJdABnGOzS7RXsgRMl2jL6ewsPe6rxEedKh/out-2%20%282%29.png" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-02-10T19:22:27.334982Z", "created_at": "2023-02-10T19:06:05.076037Z", "data_removed": false, "error": null, "id": "mbell7jvjvav5etay3cqljruaa", "input": { "image": "https://replicate.delivery/pbxt/II7KEI8StSKyHAJdABnGOzS7RXsgRMl2jL6ewsPe6rxEedKh/out-2%20%282%29.png" }, "logs": "total 60\n-rw-r--r-- 1 root root 58583 Feb 10 19:09 image.jpg\nrunning on device 0\n0%| | 0/1 [00:00<?, ?it/s]Current Source ==> image\nRunning depth extraction at 1676056168.4973645\nBoostingMonocularDepth/inputs/*.jpg\nBoostingMonocularDepth/outputs/*.png\ndevice: cuda\nNamespace(Final=True, R0=False, R20=False, colorize_results=False, data_dir='inputs/', depthNet=0, max_res=inf, net_receptive_field_size=None, output_dir='outputs', output_resolution=1, pix2pixsize=1024, savepatchs=0, savewholeest=0)\n----------------- Options ---------------\nFinal: True \t[default: False]\nR0: False\nR20: False\naspect_ratio: 1.0\nbatch_size: 1\ncheckpoints_dir: ./pix2pix/checkpoints\ncolorize_results: False\ncrop_size: 672\ndata_dir: inputs/ \t[default: None]\ndataroot: None\ndataset_mode: depthmerge\ndepthNet: 0 \t[default: None]\ndirection: AtoB\ndisplay_winsize: 256\nepoch: latest\neval: False\ngeneratevideo: None\ngpu_ids: 0\ninit_gain: 0.02\ninit_type: normal\ninput_nc: 2\nisTrain: False \t[default: None]\nload_iter: 0 \t[default: 0]\nload_size: 672\nmax_dataset_size: 10000\nmax_res: inf\nmodel: pix2pix4depth\nn_layers_D: 3\nname: void\nndf: 64\nnetD: basic\nnetG: unet_1024\nnet_receptive_field_size: None\nngf: 64\nno_dropout: False\nno_flip: False\nnorm: none\nnum_test: 50\nnum_threads: 4\noutput_dir: outputs \t[default: None]\noutput_nc: 1\noutput_resolution: None\nphase: test\npix2pixsize: None\npreprocess: resize_and_crop\nsavecrops: None\nsavewholeest: None\nserial_batches: False\nsuffix:\nverbose: False\n----------------- End -------------------\ninitialize network with normal\nloading the model from ./pix2pix/checkpoints/mergemodel/latest_net_G.pth\nLoading weights: midas/model.pt\nDownloading: \"https://github.com/facebookresearch/WSL-Images/zipball/main\" to /root/.cache/torch/hub/main.zip\nDownloading: \"https://download.pytorch.org/models/ig_resnext101_32x8-c38310e5.pth\" to /root/.cache/torch/hub/checkpoints/ig_resnext101_32x8-c38310e5.pth\n 0%| | 0.00/340M [00:00<?, ?B/s]\n 2%|▏ | 7.29M/340M [00:00<00:04, 76.4MB/s]\n 7%|▋ | 24.8M/340M [00:00<00:02, 139MB/s] \n 12%|█▏ | 40.9M/340M [00:00<00:02, 153MB/s]\n 17%|█▋ | 56.4M/340M [00:00<00:01, 157MB/s]\n 22%|██▏ | 73.5M/340M [00:00<00:01, 165MB/s]\n 27%|██▋ | 91.6M/340M [00:00<00:01, 173MB/s]\n 32%|███▏ | 110M/340M [00:00<00:01, 178MB/s] \n 38%|███▊ | 127M/340M [00:00<00:01, 181MB/s]\n 43%|████▎ | 147M/340M [00:00<00:01, 188MB/s]\n 49%|████▊ | 165M/340M [00:01<00:00, 187MB/s]\n 54%|█████▍ | 184M/340M [00:01<00:00, 192MB/s]\n 60%|█████▉ | 203M/340M [00:01<00:00, 195MB/s]\n 65%|██████▌ | 222M/340M [00:01<00:00, 185MB/s]\n 71%|███████ | 240M/340M [00:01<00:00, 185MB/s]\n 76%|███████▌ | 258M/340M [00:01<00:00, 188MB/s]\n 82%|████████▏ | 279M/340M [00:01<00:00, 196MB/s]\n 89%|████████▊ | 301M/340M [00:01<00:00, 206MB/s]\n 94%|█████████▍| 320M/340M [00:01<00:00, 194MB/s]\n100%|██████████| 340M/340M [00:01<00:00, 184MB/s]\nstart processing\nprocessing image 0 : image\nwholeImage being processed in : 1344\nAdjust factor is: 1.0\nSelecting patchs ...\nTarget resolution: (2688, 2688, 3)\nDynamicly change merged-in resolution; scale: 0.19047619047619047\nResulted depthmap res will be : (512, 512)\npatchs to process: 20\n\t processing patch 0 | [ 0 0 366 366]\n\t processing patch 1 | [ 0 55 366 366]\n\t processing patch 2 | [ 0 110 366 366]\n\t processing patch 3 | [ 0 0 256 256]\n\t processing patch 4 | [ 0 55 256 256]\n\t processing patch 5 | [ 0 110 256 256]\n\t processing patch 6 | [ 0 165 256 256]\n\t processing patch 7 | [ 0 219 256 256]\n\t processing patch 8 | [ 55 0 256 256]\n\t processing patch 9 | [293 128 219 219]\n\t processing patch 10 | [ 0 0 146 146]\n\t processing patch 11 | [ 0 55 146 146]\n\t processing patch 12 | [ 0 110 146 146]\n\t processing patch 13 | [ 0 165 146 146]\n\t processing patch 14 | [ 0 219 146 146]\n\t processing patch 15 | [ 0 274 146 146]\n\t processing patch 16 | [ 0 329 146 146]\n\t processing patch 17 | [ 55 0 146 146]\n\t processing patch 18 | [274 0 146 146]\n\t processing patch 19 | [329 0 146 146]\nfinished\nStart Running 3D_Photo ...\nLoading edge model at 1676056230.7278993\nLoading depth model at 1676056234.1163204\nLoading rgb model at 1676056235.8018358\nWriting depth ply (and basically doing everything) at 1676056237.2654574\nwriting\nWriting mesh file mesh/image.ply ...\nMaking video at 1676056476.9746718\nfov: 53.13010235415598\nMoviepy - Building video video/image_dolly-zoom-in.mp4.\n 0%| | 0/1 [07:09<?, ?it/s]\nMoviepy - Writing video video/image_dolly-zoom-in.mp4\n 0%| | 0/1 [07:09<?, ?it/s]\nt: 0%| | 0/120 [00:00<?, ?it/s, now=None]\u001b[A\nt: 2%|▎ | 3/120 [00:00<00:05, 20.55it/s, now=None]\u001b[A\nt: 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now=None]\u001b[A\nt: 51%|█████ | 61/120 [00:00<00:00, 114.34it/s, now=None]\u001b[A\nt: 62%|██████▏ | 74/120 [00:00<00:00, 117.92it/s, now=None]\u001b[A\nt: 72%|███████▎ | 87/120 [00:00<00:00, 121.03it/s, now=None]\u001b[A\nt: 85%|████████▌ | 102/120 [00:00<00:00, 128.05it/s, now=None]\u001b[A\nt: 97%|█████████▋| 116/120 [00:00<00:00, 130.73it/s, now=None]\u001b[A\n \u001b[A\nMoviepy - Done !\n 0%| | 0/1 [08:58<?, ?it/s]\nMoviepy - video ready video/image_zoom-in.mp4\n 0%| | 0/1 [08:58<?, ?it/s]\nMoviepy - Building video video/image_circle.mp4.\n0%| | 0/1 [10:53<?, ?it/s]\nMoviepy - Writing video video/image_circle.mp4\n 0%| | 0/1 [10:53<?, ?it/s]\nt: 0%| | 0/120 [00:00<?, ?it/s, now=None]\u001b[A\nt: 2%|▏ | 2/120 [00:00<00:05, 19.92it/s, now=None]\u001b[A\nt: 12%|█▏ | 14/120 [00:00<00:01, 76.57it/s, now=None]\u001b[A\nt: 28%|██▊ | 34/120 [00:00<00:00, 129.42it/s, now=None]\u001b[A\nt: 40%|████ | 48/120 [00:00<00:00, 106.51it/s, now=None]\u001b[A\nt: 52%|█████▏ | 62/120 [00:00<00:00, 116.59it/s, now=None]\u001b[A\nt: 62%|██████▎ | 75/120 [00:00<00:00, 114.71it/s, now=None]\u001b[A\nt: 73%|███████▎ | 88/120 [00:00<00:00, 113.82it/s, now=None]\u001b[A\nt: 84%|████████▍ | 101/120 [00:00<00:00, 118.02it/s, now=None]\u001b[A\nt: 94%|█████████▍| 113/120 [00:01<00:00, 118.09it/s, now=None]\u001b[A\n \u001b[A\nMoviepy - Done !\n 0%| | 0/1 [10:55<?, ?it/s]\nMoviepy - video ready video/image_circle.mp4\n 0%| | 0/1 [10:55<?, ?it/s]\nMoviepy - Building video video/image_swing.mp4.\n0%| | 0/1 [12:46<?, ?it/s]\nMoviepy - Writing video video/image_swing.mp4\n 0%| | 0/1 [12:46<?, ?it/s]\nt: 0%| | 0/120 [00:00<?, ?it/s, now=None]\u001b[A\nt: 2%|▏ | 2/120 [00:00<00:08, 13.61it/s, now=None]\u001b[A\nt: 17%|█▋ | 20/120 [00:00<00:01, 92.85it/s, now=None]\u001b[A\nt: 30%|███ | 36/120 [00:00<00:00, 116.69it/s, now=None]\u001b[A\nt: 41%|████ | 49/120 [00:00<00:00, 89.85it/s, now=None] \u001b[A\nt: 52%|█████▎ | 63/120 [00:00<00:00, 103.36it/s, now=None]\u001b[A\nt: 62%|██████▎ | 75/120 [00:00<00:00, 101.40it/s, now=None]\u001b[A\nt: 72%|███████▏ | 86/120 [00:00<00:00, 93.93it/s, now=None] \u001b[A\nt: 81%|████████ | 97/120 [00:01<00:00, 92.81it/s, now=None]\u001b[A\nt: 89%|████████▉ | 107/120 [00:01<00:00, 93.75it/s, now=None]\u001b[A\nt: 100%|██████████| 120/120 [00:01<00:00, 97.20it/s, now=None]\u001b[A\n \u001b[A\nMoviepy - Done !\n0%| | 0/1 [12:48<?, ?it/s]\nMoviepy - video ready video/image_swing.mp4\n0%| | 0/1 [12:48<?, ?it/s]\n100%|██████████| 1/1 [12:48<00:00, 768.44s/it]\n100%|██████████| 1/1 [12:48<00:00, 768.44s/it]\ntotal 1548\n-rw-r--r-- 1 root root 482311 Feb 10 19:20 image_circle.mp4\n-rw-r--r-- 1 root root 319095 Feb 10 19:16 image_dolly-zoom-in.mp4\n-rw-r--r-- 1 root root 439614 Feb 10 19:22 image_swing.mp4\n-rw-r--r-- 1 root root 338003 Feb 10 19:18 image_zoom-in.mp4", "metrics": { "predict_time": 791.544949, "total_time": 982.258945 }, "output": [ "https://replicate.delivery/pbxt/X2bn2QmgY27eHip2gykPVf5QYTfGATXNnDLR9u9VgWLe2S0BB/image_circle.mp4", "https://replicate.delivery/pbxt/MX3wk4LO3ZZWHxbgN3G4aFBk9hlW6e7u4GvB12mBeQehbJ6gA/image_dolly-zoom-in.mp4", "https://replicate.delivery/pbxt/Z5DoK70dNRpGNZwZpFvdVgrVMFRgZFkkmHXNUziC82VcLRHE/image_swing.mp4", "https://replicate.delivery/pbxt/crt7flSZZekGFUeij5ZwdVYLhbZZ1xb2KEfjef1HNDXScLRHE/image_zoom-in.mp4", "https://replicate.delivery/pbxt/j7v3kuyJdgJtL9fN2lirY9l57eJU1PbTMuE64L02Q0ejbJ6gA/image.png", "https://replicate.delivery/pbxt/pAAb11OeU1VTf0svSU9pFlNcJG4UaZ9vvk2aQuZ14ChxtEdQA/temp.dat" ], "started_at": "2023-02-10T19:09:15.790033Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mbell7jvjvav5etay3cqljruaa", "cancel": "https://api.replicate.com/v1/predictions/mbell7jvjvav5etay3cqljruaa/cancel" }, "version": "f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de" }Generated intotal 60 -rw-r--r-- 1 root root 58583 Feb 10 19:09 image.jpg running on device 0 0%| | 0/1 [00:00<?, ?it/s]Current Source ==> image Running depth extraction at 1676056168.4973645 BoostingMonocularDepth/inputs/*.jpg BoostingMonocularDepth/outputs/*.png device: cuda Namespace(Final=True, R0=False, R20=False, colorize_results=False, data_dir='inputs/', depthNet=0, max_res=inf, net_receptive_field_size=None, output_dir='outputs', output_resolution=1, pix2pixsize=1024, savepatchs=0, savewholeest=0) ----------------- Options --------------- Final: True [default: False] R0: False R20: False aspect_ratio: 1.0 batch_size: 1 checkpoints_dir: ./pix2pix/checkpoints colorize_results: False crop_size: 672 data_dir: inputs/ [default: None] dataroot: None dataset_mode: depthmerge depthNet: 0 [default: None] direction: AtoB display_winsize: 256 epoch: latest eval: False generatevideo: None gpu_ids: 0 init_gain: 0.02 init_type: normal input_nc: 2 isTrain: False [default: None] load_iter: 0 [default: 0] load_size: 672 max_dataset_size: 10000 max_res: inf model: pix2pix4depth n_layers_D: 3 name: void ndf: 64 netD: basic netG: unet_1024 net_receptive_field_size: None ngf: 64 no_dropout: False no_flip: False norm: none num_test: 50 num_threads: 4 output_dir: outputs [default: None] output_nc: 1 output_resolution: None phase: test pix2pixsize: None preprocess: resize_and_crop savecrops: None savewholeest: None serial_batches: False suffix: verbose: False ----------------- End ------------------- initialize network with normal loading the model from ./pix2pix/checkpoints/mergemodel/latest_net_G.pth Loading weights: midas/model.pt Downloading: "https://github.com/facebookresearch/WSL-Images/zipball/main" to /root/.cache/torch/hub/main.zip Downloading: "https://download.pytorch.org/models/ig_resnext101_32x8-c38310e5.pth" to /root/.cache/torch/hub/checkpoints/ig_resnext101_32x8-c38310e5.pth 0%| | 0.00/340M [00:00<?, ?B/s] 2%|▏ | 7.29M/340M [00:00<00:04, 76.4MB/s] 7%|▋ | 24.8M/340M [00:00<00:02, 139MB/s] 12%|█▏ | 40.9M/340M [00:00<00:02, 153MB/s] 17%|█▋ | 56.4M/340M [00:00<00:01, 157MB/s] 22%|██▏ | 73.5M/340M [00:00<00:01, 165MB/s] 27%|██▋ | 91.6M/340M [00:00<00:01, 173MB/s] 32%|███▏ | 110M/340M [00:00<00:01, 178MB/s] 38%|███▊ | 127M/340M [00:00<00:01, 181MB/s] 43%|████▎ | 147M/340M [00:00<00:01, 188MB/s] 49%|████▊ | 165M/340M [00:01<00:00, 187MB/s] 54%|█████▍ | 184M/340M [00:01<00:00, 192MB/s] 60%|█████▉ | 203M/340M [00:01<00:00, 195MB/s] 65%|██████▌ | 222M/340M [00:01<00:00, 185MB/s] 71%|███████ | 240M/340M [00:01<00:00, 185MB/s] 76%|███████▌ | 258M/340M [00:01<00:00, 188MB/s] 82%|████████▏ | 279M/340M [00:01<00:00, 196MB/s] 89%|████████▊ | 301M/340M [00:01<00:00, 206MB/s] 94%|█████████▍| 320M/340M [00:01<00:00, 194MB/s] 100%|██████████| 340M/340M [00:01<00:00, 184MB/s] start processing processing image 0 : image wholeImage being processed in : 1344 Adjust factor is: 1.0 Selecting patchs ... Target resolution: (2688, 2688, 3) Dynamicly change merged-in resolution; scale: 0.19047619047619047 Resulted depthmap res will be : (512, 512) patchs to process: 20 processing patch 0 | [ 0 0 366 366] processing patch 1 | [ 0 55 366 366] processing patch 2 | [ 0 110 366 366] processing patch 3 | [ 0 0 256 256] processing patch 4 | [ 0 55 256 256] processing patch 5 | [ 0 110 256 256] processing patch 6 | [ 0 165 256 256] processing patch 7 | [ 0 219 256 256] processing patch 8 | [ 55 0 256 256] processing patch 9 | [293 128 219 219] processing patch 10 | [ 0 0 146 146] processing patch 11 | [ 0 55 146 146] processing patch 12 | [ 0 110 146 146] processing patch 13 | [ 0 165 146 146] processing patch 14 | [ 0 219 146 146] processing patch 15 | [ 0 274 146 146] processing patch 16 | [ 0 329 146 146] processing patch 17 | [ 55 0 146 146] processing patch 18 | [274 0 146 146] processing patch 19 | [329 0 146 146] finished Start Running 3D_Photo ... Loading edge model at 1676056230.7278993 Loading depth model at 1676056234.1163204 Loading rgb model at 1676056235.8018358 Writing depth ply (and basically doing everything) at 1676056237.2654574 writing Writing mesh file mesh/image.ply ... Making video at 1676056476.9746718 fov: 53.13010235415598 Moviepy - Building video video/image_dolly-zoom-in.mp4. 0%| | 0/1 [07:09<?, ?it/s] Moviepy - Writing video video/image_dolly-zoom-in.mp4 0%| | 0/1 [07:09<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 2%|▎ | 3/120 [00:00<00:05, 20.55it/s, now=None] t: 19%|█▉ | 23/120 [00:00<00:00, 107.56it/s, now=None] t: 36%|███▌ | 43/120 [00:00<00:00, 144.35it/s, now=None] t: 49%|████▉ | 59/120 [00:00<00:00, 121.75it/s, now=None] t: 62%|██████▏ | 74/120 [00:00<00:00, 129.13it/s, now=None] t: 76%|███████▌ | 91/120 [00:00<00:00, 140.97it/s, now=None] t: 88%|████████▊ | 106/120 [00:00<00:00, 142.86it/s, now=None] Moviepy - Done ! 0%| | 0/1 [07:11<?, ?it/s] Moviepy - video ready video/image_dolly-zoom-in.mp4 0%| | 0/1 [07:11<?, ?it/s] Moviepy - Building video video/image_zoom-in.mp4. 0%| | 0/1 [08:56<?, ?it/s] Moviepy - Writing video video/image_zoom-in.mp4 0%| | 0/1 [08:56<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 2%|▏ | 2/120 [00:00<00:06, 18.67it/s, now=None] t: 11%|█ | 13/120 [00:00<00:01, 69.66it/s, now=None] t: 27%|██▋ | 32/120 [00:00<00:00, 122.63it/s, now=None] t: 40%|████ | 48/120 [00:00<00:00, 108.55it/s, now=None] t: 51%|█████ | 61/120 [00:00<00:00, 114.34it/s, now=None] t: 62%|██████▏ | 74/120 [00:00<00:00, 117.92it/s, now=None] t: 72%|███████▎ | 87/120 [00:00<00:00, 121.03it/s, now=None] t: 85%|████████▌ | 102/120 [00:00<00:00, 128.05it/s, now=None] t: 97%|█████████▋| 116/120 [00:00<00:00, 130.73it/s, now=None] Moviepy - Done ! 0%| | 0/1 [08:58<?, ?it/s] Moviepy - video ready video/image_zoom-in.mp4 0%| | 0/1 [08:58<?, ?it/s] Moviepy - Building video video/image_circle.mp4. 0%| | 0/1 [10:53<?, ?it/s] Moviepy - Writing video video/image_circle.mp4 0%| | 0/1 [10:53<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 2%|▏ | 2/120 [00:00<00:05, 19.92it/s, now=None] t: 12%|█▏ | 14/120 [00:00<00:01, 76.57it/s, now=None] t: 28%|██▊ | 34/120 [00:00<00:00, 129.42it/s, now=None] t: 40%|████ | 48/120 [00:00<00:00, 106.51it/s, now=None] t: 52%|█████▏ | 62/120 [00:00<00:00, 116.59it/s, now=None] t: 62%|██████▎ | 75/120 [00:00<00:00, 114.71it/s, now=None] t: 73%|███████▎ | 88/120 [00:00<00:00, 113.82it/s, now=None] t: 84%|████████▍ | 101/120 [00:00<00:00, 118.02it/s, now=None] t: 94%|█████████▍| 113/120 [00:01<00:00, 118.09it/s, now=None] Moviepy - Done ! 0%| | 0/1 [10:55<?, ?it/s] Moviepy - video ready video/image_circle.mp4 0%| | 0/1 [10:55<?, ?it/s] Moviepy - Building video video/image_swing.mp4. 0%| | 0/1 [12:46<?, ?it/s] Moviepy - Writing video video/image_swing.mp4 0%| | 0/1 [12:46<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 2%|▏ | 2/120 [00:00<00:08, 13.61it/s, now=None] t: 17%|█▋ | 20/120 [00:00<00:01, 92.85it/s, now=None] t: 30%|███ | 36/120 [00:00<00:00, 116.69it/s, now=None] t: 41%|████ | 49/120 [00:00<00:00, 89.85it/s, now=None] t: 52%|█████▎ | 63/120 [00:00<00:00, 103.36it/s, now=None] t: 62%|██████▎ | 75/120 [00:00<00:00, 101.40it/s, now=None] t: 72%|███████▏ | 86/120 [00:00<00:00, 93.93it/s, now=None] t: 81%|████████ | 97/120 [00:01<00:00, 92.81it/s, now=None] t: 89%|████████▉ | 107/120 [00:01<00:00, 93.75it/s, now=None] t: 100%|██████████| 120/120 [00:01<00:00, 97.20it/s, now=None] Moviepy - Done ! 0%| | 0/1 [12:48<?, ?it/s] Moviepy - video ready video/image_swing.mp4 0%| | 0/1 [12:48<?, ?it/s] 100%|██████████| 1/1 [12:48<00:00, 768.44s/it] 100%|██████████| 1/1 [12:48<00:00, 768.44s/it] total 1548 -rw-r--r-- 1 root root 482311 Feb 10 19:20 image_circle.mp4 -rw-r--r-- 1 root root 319095 Feb 10 19:16 image_dolly-zoom-in.mp4 -rw-r--r-- 1 root root 439614 Feb 10 19:22 image_swing.mp4 -rw-r--r-- 1 root root 338003 Feb 10 19:18 image_zoom-in.mp4Prediction
pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9deIDvm6shw6lmnh2faelgobrqcz2vuStatusSucceededSourceWebHardware–Total durationCreatedInput
- image
{ "image": "https://replicate.delivery/pbxt/IIA6VnZHsCMPJ5XI9Vuywl6Jsp7Kbz7ZaDeLjryGavSzopuN/Hell._Hyperdetailed_intricately_detailed_cinematic_lighting._By_Salvador_.jpg" }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 pollinations/3d-photo-inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de", { input: { image: "https://replicate.delivery/pbxt/IIA6VnZHsCMPJ5XI9Vuywl6Jsp7Kbz7ZaDeLjryGavSzopuN/Hell._Hyperdetailed_intricately_detailed_cinematic_lighting._By_Salvador_.jpg" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);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 pollinations/3d-photo-inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de", input={ "image": "https://replicate.delivery/pbxt/IIA6VnZHsCMPJ5XI9Vuywl6Jsp7Kbz7ZaDeLjryGavSzopuN/Hell._Hyperdetailed_intricately_detailed_cinematic_lighting._By_Salvador_.jpg" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run pollinations/3d-photo-inpainting 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": "pollinations/3d-photo-inpainting:f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de", "input": { "image": "https://replicate.delivery/pbxt/IIA6VnZHsCMPJ5XI9Vuywl6Jsp7Kbz7ZaDeLjryGavSzopuN/Hell._Hyperdetailed_intricately_detailed_cinematic_lighting._By_Salvador_.jpg" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-02-10T22:18:29.892644Z", "created_at": "2023-02-10T22:07:53.852421Z", "data_removed": false, "error": null, "id": "vm6shw6lmnh2faelgobrqcz2vu", "input": { "image": "https://replicate.delivery/pbxt/IIA6VnZHsCMPJ5XI9Vuywl6Jsp7Kbz7ZaDeLjryGavSzopuN/Hell._Hyperdetailed_intricately_detailed_cinematic_lighting._By_Salvador_.jpg" }, "logs": "total 52\n-rw-r--r-- 1 root root 52789 Feb 10 22:09 image.jpg\nrunning on device 0\n0%| | 0/1 [00:00<?, ?it/s]Current Source ==> image\nRunning depth extraction at 1676066967.4100652\nBoostingMonocularDepth/inputs/*.jpg\nBoostingMonocularDepth/outputs/*.png\ndevice: cuda\nNamespace(Final=True, R0=False, R20=False, colorize_results=False, data_dir='inputs/', depthNet=0, max_res=inf, net_receptive_field_size=None, output_dir='outputs', output_resolution=1, pix2pixsize=1024, savepatchs=0, savewholeest=0)\n----------------- Options ---------------\nFinal: True \t[default: False]\nR0: False\nR20: False\naspect_ratio: 1.0\nbatch_size: 1\ncheckpoints_dir: ./pix2pix/checkpoints\ncolorize_results: False\ncrop_size: 672\ndata_dir: inputs/ \t[default: None]\ndataroot: None\ndataset_mode: depthmerge\ndepthNet: 0 \t[default: None]\ndirection: AtoB\ndisplay_winsize: 256\nepoch: latest\neval: False\ngeneratevideo: None\ngpu_ids: 0\ninit_gain: 0.02\ninit_type: normal\ninput_nc: 2\nisTrain: False \t[default: None]\nload_iter: 0 \t[default: 0]\nload_size: 672\nmax_dataset_size: 10000\nmax_res: inf\nmodel: pix2pix4depth\nn_layers_D: 3\nname: void\nndf: 64\nnetD: basic\nnetG: unet_1024\nnet_receptive_field_size: None\nngf: 64\nno_dropout: False\nno_flip: False\nnorm: none\nnum_test: 50\nnum_threads: 4\noutput_dir: outputs \t[default: None]\noutput_nc: 1\noutput_resolution: None\nphase: test\npix2pixsize: None\npreprocess: resize_and_crop\nsavecrops: None\nsavewholeest: None\nserial_batches: False\nsuffix:\nverbose: False\n----------------- End -------------------\ninitialize network with normal\nloading the model from ./pix2pix/checkpoints/mergemodel/latest_net_G.pth\nLoading weights: midas/model.pt\nDownloading: \"https://github.com/facebookresearch/WSL-Images/zipball/main\" to /root/.cache/torch/hub/main.zip\nDownloading: \"https://download.pytorch.org/models/ig_resnext101_32x8-c38310e5.pth\" to /root/.cache/torch/hub/checkpoints/ig_resnext101_32x8-c38310e5.pth\n 0%| | 0.00/340M [00:00<?, ?B/s]\n 2%|▏ | 6.51M/340M [00:00<00:05, 68.2MB/s]\n 5%|▍ | 16.3M/340M [00:00<00:03, 88.3MB/s]\n 8%|▊ | 25.9M/340M [00:00<00:03, 93.8MB/s]\n 10%|█ | 35.1M/340M [00:00<00:03, 94.9MB/s]\n 13%|█▎ | 44.2M/340M [00:00<00:03, 91.5MB/s]\n 16%|█▌ | 53.2M/340M [00:00<00:03, 92.7MB/s]\n 18%|█▊ | 62.8M/340M [00:00<00:03, 95.2MB/s]\n 21%|██▏ | 72.3M/340M [00:00<00:02, 96.6MB/s]\n 24%|██▍ | 82.0M/340M [00:00<00:02, 98.2MB/s]\n 27%|██▋ | 91.8M/340M [00:01<00:02, 99.5MB/s]\n 30%|██▉ | 101M/340M [00:01<00:02, 99.7MB/s] \n 33%|███▎ | 111M/340M [00:01<00:02, 101MB/s] \n 36%|███▌ | 121M/340M [00:01<00:02, 101MB/s]\n 38%|███▊ | 130M/340M [00:01<00:02, 101MB/s]\n 41%|████▏ | 140M/340M [00:01<00:02, 101MB/s]\n 44%|████▍ | 150M/340M [00:01<00:01, 101MB/s]\n 47%|████▋ | 160M/340M [00:01<00:01, 101MB/s]\n 50%|████▉ | 169M/340M [00:01<00:01, 101MB/s]\n 53%|█████▎ | 179M/340M [00:01<00:01, 101MB/s]\n 56%|█████▌ | 189M/340M [00:02<00:01, 101MB/s]\n 58%|█████▊ | 198M/340M [00:02<00:01, 99.5MB/s]\n 61%|██████▏ | 208M/340M [00:02<00:01, 100MB/s] \n 64%|██████▍ | 218M/340M [00:02<00:01, 101MB/s]\n 67%|██████▋ | 227M/340M [00:02<00:01, 101MB/s]\n 70%|██████▉ | 237M/340M [00:02<00:01, 98.7MB/s]\n 73%|███████▎ | 247M/340M [00:02<00:00, 99.6MB/s]\n 75%|███████▌ | 256M/340M [00:02<00:00, 98.9MB/s]\n 78%|███████▊ | 266M/340M [00:02<00:00, 98.8MB/s]\n 81%|████████ | 275M/340M [00:02<00:00, 98.9MB/s]\n 84%|████████▍ | 285M/340M [00:03<00:00, 99.8MB/s]\n 87%|████████▋ | 294M/340M [00:03<00:00, 99.4MB/s]\n 89%|████████▉ | 304M/340M [00:03<00:00, 94.2MB/s]\n 92%|█████████▏| 314M/340M [00:03<00:00, 96.2MB/s]\n 95%|█████████▌| 323M/340M [00:03<00:00, 95.8MB/s]\n 98%|█████████▊| 332M/340M [00:03<00:00, 97.6MB/s]\n100%|██████████| 340M/340M [00:03<00:00, 98.1MB/s]\nstart processing\nprocessing image 0 : image\nwholeImage being processed in : 1344\nAdjust factor is: 1.0\nSelecting patchs ...\nTarget resolution: (2688, 2688, 3)\nDynamicly change merged-in resolution; scale: 0.19047619047619047\nResulted depthmap res will be : (512, 512)\npatchs to process: 34\n\t processing patch 0 | [ 0 0 475 475]\n\t processing patch 1 | [ 18 73 439 439]\n\t processing patch 2 | [ 73 18 439 439]\n\t processing patch 3 | [ 73 73 439 439]\n\t processing patch 4 | [ 0 0 366 366]\n\t processing patch 5 | [ 0 55 366 366]\n\t processing patch 6 | [ 0 110 366 366]\n\t processing patch 7 | [ 55 0 366 366]\n\t processing patch 8 | [ 18 183 329 329]\n\t processing patch 9 | [ 73 183 329 329]\n\t processing patch 10 | [128 183 329 329]\n\t processing patch 11 | [183 128 329 329]\n\t processing patch 12 | [183 183 329 329]\n\t processing patch 13 | [ 0 0 256 256]\n\t processing patch 14 | [ 0 55 256 256]\n\t processing patch 15 | [ 0 110 256 256]\n\t processing patch 16 | [ 0 165 256 256]\n\t processing patch 17 | [ 0 219 256 256]\nprocessing patch 18 | [ 55 0 256 256]\n\t processing patch 19 | [110 0 256 256]\n\t processing patch 20 | [ 18 293 219 219]\n\t processing patch 21 | [ 73 293 219 219]\nprocessing patch 22 | [128 293 219 219]\n\t processing patch 23 | [183 293 219 219]\n\t processing patch 24 | [238 293 219 219]\n\t processing patch 25 | [293 183 219 219]\n\t processing patch 26 | [293 238 219 219]\n\t processing patch 27 | [323 323 158 158]\n\t processing patch 28 | [ 0 110 146 146]\n\t processing patch 29 | [ 0 165 146 146]\n\t processing patch 30 | [ 0 219 146 146]\n\t processing patch 31 | [ 0 274 146 146]\nprocessing patch 32 | [110 0 146 146]\n\t processing patch 33 | [165 0 146 146]\nfinished\nStart Running 3D_Photo ...\nLoading edge model at 1676067019.1191473\nLoading depth model at 1676067021.3657682\nLoading rgb model at 1676067022.2461312\nWriting depth ply (and basically doing everything) at 1676067023.0791702\nwriting\nWriting mesh file mesh/image.ply ...\nMaking video at 1676067164.620918\nfov: 53.13010235415598\nMoviepy - Building video video/image_dolly-zoom-in.mp4.\n 0%| | 0/1 [04:41<?, ?it/s]\nMoviepy - Writing video video/image_dolly-zoom-in.mp4\n 0%| | 0/1 [04:41<?, ?it/s]\nt: 0%| | 0/120 [00:00<?, ?it/s, now=None]\u001b[A\nt: 2%|▎ | 3/120 [00:00<00:04, 23.96it/s, now=None]\u001b[A\nt: 28%|██▊ | 33/120 [00:00<00:00, 170.09it/s, now=None]\u001b[A\nt: 43%|████▎ | 52/120 [00:00<00:00, 172.39it/s, now=None]\u001b[A\nt: 59%|█████▉ | 71/120 [00:00<00:00, 174.31it/s, now=None]\u001b[A\nt: 74%|███████▍ | 89/120 [00:00<00:00, 171.63it/s, now=None]\u001b[A\nt: 89%|████████▉ | 107/120 [00:00<00:00, 172.74it/s, now=None]\u001b[A\n \u001b[A\nMoviepy - Done !\n 0%| | 0/1 [04:43<?, ?it/s]\nMoviepy - video ready video/image_dolly-zoom-in.mp4\n 0%| | 0/1 [04:43<?, ?it/s]\nMoviepy - Building video video/image_zoom-in.mp4.\n0%| | 0/1 [06:03<?, ?it/s]\nMoviepy - Writing video video/image_zoom-in.mp4\n 0%| | 0/1 [06:03<?, ?it/s]\nt: 0%| | 0/120 [00:00<?, ?it/s, now=None]\u001b[A\nt: 22%|██▎ | 27/120 [00:00<00:00, 266.32it/s, now=None]\u001b[A\nt: 45%|████▌ | 54/120 [00:00<00:00, 179.66it/s, now=None]\u001b[A\nt: 62%|██████▏ | 74/120 [00:00<00:00, 178.36it/s, now=None]\u001b[A\nt: 78%|███████▊ | 93/120 [00:00<00:00, 179.47it/s, now=None]\u001b[A\nt: 93%|█████████▎| 112/120 [00:00<00:00, 161.27it/s, now=None]\u001b[A\n \u001b[A\nMoviepy - Done !\n 0%| | 0/1 [06:04<?, ?it/s]\nMoviepy - video ready video/image_zoom-in.mp4\n 0%| | 0/1 [06:04<?, ?it/s]\nMoviepy - Building video video/image_circle.mp4.\n0%| | 0/1 [07:28<?, ?it/s]\nMoviepy - Writing video video/image_circle.mp4\n 0%| | 0/1 [07:28<?, ?it/s]\nt: 0%| | 0/120 [00:00<?, ?it/s, now=None]\u001b[A\nt: 24%|██▍ | 29/120 [00:00<00:00, 285.58it/s, now=None]\u001b[A\nt: 48%|████▊ | 58/120 [00:00<00:00, 186.34it/s, now=None]\u001b[A\nt: 66%|██████▌ | 79/120 [00:00<00:00, 177.51it/s, now=None]\u001b[A\nt: 82%|████████▏ | 98/120 [00:00<00:00, 165.16it/s, now=None]\u001b[A\nt: 97%|█████████▋| 116/120 [00:00<00:00, 155.31it/s, now=None]\u001b[A\n \u001b[A\nMoviepy - Done !\n 0%| | 0/1 [07:30<?, ?it/s]\nMoviepy - video ready video/image_circle.mp4\n 0%| | 0/1 [07:30<?, ?it/s]\nMoviepy - Building video video/image_swing.mp4.\n0%| | 0/1 [08:54<?, ?it/s]\nMoviepy - Writing video video/image_swing.mp4\n 0%| | 0/1 [08:54<?, ?it/s]\nt: 0%| | 0/120 [00:00<?, ?it/s, now=None]\u001b[A\nt: 24%|██▍ | 29/120 [00:00<00:00, 283.42it/s, now=None]\u001b[A\nt: 48%|████▊ | 58/120 [00:00<00:00, 196.96it/s, now=None]\u001b[A\nt: 67%|██████▋ | 80/120 [00:00<00:00, 183.06it/s, now=None]\u001b[A\nt: 83%|████████▎ | 100/120 [00:00<00:00, 174.52it/s, now=None]\u001b[A\nt: 98%|█████████▊| 118/120 [00:00<00:00, 166.56it/s, now=None]\u001b[A\n \u001b[A\nMoviepy - Done !\n 0%| | 0/1 [08:56<?, ?it/s]\nMoviepy - video ready video/image_swing.mp4\n 0%| | 0/1 [08:56<?, ?it/s]\n100%|██████████| 1/1 [08:56<00:00, 536.11s/it]\n100%|██████████| 1/1 [08:56<00:00, 536.11s/it]\ntotal 1160\n-rw-r--r-- 1 root root 356648 Feb 10 22:16 image_circle.mp4\n-rw-r--r-- 1 root root 244326 Feb 10 22:14 image_dolly-zoom-in.mp4\n-rw-r--r-- 1 root root 321436 Feb 10 22:18 image_swing.mp4\n-rw-r--r-- 1 root root 255991 Feb 10 22:15 image_zoom-in.mp4", "metrics": { "predict_time": 548.786024, "total_time": 636.040223 }, "output": [ "https://replicate.delivery/pbxt/yfYfGGnqj6uoY0lHceh0QrxF2knuLyaaYXg2Vo99M73mlO6gA/image_circle.mp4", "https://replicate.delivery/pbxt/OtujYqQULyqfdCErL7wT7wSCDffxviPZbUMbDb6KpZdolO6gA/image_dolly-zoom-in.mp4", "https://replicate.delivery/pbxt/ml0qJigOK75pI5QEhussVGPcbCboJ22SLu3XS9Yy5KCt0RHE/image_swing.mp4", "https://replicate.delivery/pbxt/FAfogsTLLC26LK5xhd2EyO3e5PEeJiGTzbneqJuhbPYRLd0BB/image_zoom-in.mp4", "https://replicate.delivery/pbxt/RyAQPi2I0EJlPBmSOfL7VYar7F9NxJybETlPDlqemkP1SHdQA/image.png", "https://replicate.delivery/pbxt/cjUSmqmfszUZJqndVxSL83erPT8Kytz05ay62UydEVc1SHdQA/temp.dat" ], "started_at": "2023-02-10T22:09:21.106620Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vm6shw6lmnh2faelgobrqcz2vu", "cancel": "https://api.replicate.com/v1/predictions/vm6shw6lmnh2faelgobrqcz2vu/cancel" }, "version": "f23891d1e3174b711e1a81c3bbf24a9903d03eeee3ce64dbb97947aa78a4f9de" }Generated intotal 52 -rw-r--r-- 1 root root 52789 Feb 10 22:09 image.jpg running on device 0 0%| | 0/1 [00:00<?, ?it/s]Current Source ==> image Running depth extraction at 1676066967.4100652 BoostingMonocularDepth/inputs/*.jpg BoostingMonocularDepth/outputs/*.png device: cuda Namespace(Final=True, R0=False, R20=False, colorize_results=False, data_dir='inputs/', depthNet=0, max_res=inf, net_receptive_field_size=None, output_dir='outputs', output_resolution=1, pix2pixsize=1024, savepatchs=0, savewholeest=0) ----------------- Options --------------- Final: True [default: False] R0: False R20: False aspect_ratio: 1.0 batch_size: 1 checkpoints_dir: ./pix2pix/checkpoints colorize_results: False crop_size: 672 data_dir: inputs/ [default: None] dataroot: None dataset_mode: depthmerge depthNet: 0 [default: None] direction: AtoB display_winsize: 256 epoch: latest eval: False generatevideo: None gpu_ids: 0 init_gain: 0.02 init_type: normal input_nc: 2 isTrain: False [default: None] load_iter: 0 [default: 0] load_size: 672 max_dataset_size: 10000 max_res: inf model: pix2pix4depth n_layers_D: 3 name: void ndf: 64 netD: basic netG: unet_1024 net_receptive_field_size: None ngf: 64 no_dropout: False no_flip: False norm: none num_test: 50 num_threads: 4 output_dir: outputs [default: None] output_nc: 1 output_resolution: None phase: test pix2pixsize: None preprocess: resize_and_crop savecrops: None savewholeest: None serial_batches: False suffix: verbose: False ----------------- End ------------------- initialize network with normal loading the model from ./pix2pix/checkpoints/mergemodel/latest_net_G.pth Loading weights: midas/model.pt Downloading: "https://github.com/facebookresearch/WSL-Images/zipball/main" to /root/.cache/torch/hub/main.zip Downloading: "https://download.pytorch.org/models/ig_resnext101_32x8-c38310e5.pth" to /root/.cache/torch/hub/checkpoints/ig_resnext101_32x8-c38310e5.pth 0%| | 0.00/340M [00:00<?, ?B/s] 2%|▏ | 6.51M/340M [00:00<00:05, 68.2MB/s] 5%|▍ | 16.3M/340M [00:00<00:03, 88.3MB/s] 8%|▊ | 25.9M/340M [00:00<00:03, 93.8MB/s] 10%|█ | 35.1M/340M [00:00<00:03, 94.9MB/s] 13%|█▎ | 44.2M/340M [00:00<00:03, 91.5MB/s] 16%|█▌ | 53.2M/340M [00:00<00:03, 92.7MB/s] 18%|█▊ | 62.8M/340M [00:00<00:03, 95.2MB/s] 21%|██▏ | 72.3M/340M [00:00<00:02, 96.6MB/s] 24%|██▍ | 82.0M/340M [00:00<00:02, 98.2MB/s] 27%|██▋ | 91.8M/340M [00:01<00:02, 99.5MB/s] 30%|██▉ | 101M/340M [00:01<00:02, 99.7MB/s] 33%|███▎ | 111M/340M [00:01<00:02, 101MB/s] 36%|███▌ | 121M/340M [00:01<00:02, 101MB/s] 38%|███▊ | 130M/340M [00:01<00:02, 101MB/s] 41%|████▏ | 140M/340M [00:01<00:02, 101MB/s] 44%|████▍ | 150M/340M [00:01<00:01, 101MB/s] 47%|████▋ | 160M/340M [00:01<00:01, 101MB/s] 50%|████▉ | 169M/340M [00:01<00:01, 101MB/s] 53%|█████▎ | 179M/340M [00:01<00:01, 101MB/s] 56%|█████▌ | 189M/340M [00:02<00:01, 101MB/s] 58%|█████▊ | 198M/340M [00:02<00:01, 99.5MB/s] 61%|██████▏ | 208M/340M [00:02<00:01, 100MB/s] 64%|██████▍ | 218M/340M [00:02<00:01, 101MB/s] 67%|██████▋ | 227M/340M [00:02<00:01, 101MB/s] 70%|██████▉ | 237M/340M [00:02<00:01, 98.7MB/s] 73%|███████▎ | 247M/340M [00:02<00:00, 99.6MB/s] 75%|███████▌ | 256M/340M [00:02<00:00, 98.9MB/s] 78%|███████▊ | 266M/340M [00:02<00:00, 98.8MB/s] 81%|████████ | 275M/340M [00:02<00:00, 98.9MB/s] 84%|████████▍ | 285M/340M [00:03<00:00, 99.8MB/s] 87%|████████▋ | 294M/340M [00:03<00:00, 99.4MB/s] 89%|████████▉ | 304M/340M [00:03<00:00, 94.2MB/s] 92%|█████████▏| 314M/340M [00:03<00:00, 96.2MB/s] 95%|█████████▌| 323M/340M [00:03<00:00, 95.8MB/s] 98%|█████████▊| 332M/340M [00:03<00:00, 97.6MB/s] 100%|██████████| 340M/340M [00:03<00:00, 98.1MB/s] start processing processing image 0 : image wholeImage being processed in : 1344 Adjust factor is: 1.0 Selecting patchs ... Target resolution: (2688, 2688, 3) Dynamicly change merged-in resolution; scale: 0.19047619047619047 Resulted depthmap res will be : (512, 512) patchs to process: 34 processing patch 0 | [ 0 0 475 475] processing patch 1 | [ 18 73 439 439] processing patch 2 | [ 73 18 439 439] processing patch 3 | [ 73 73 439 439] processing patch 4 | [ 0 0 366 366] processing patch 5 | [ 0 55 366 366] processing patch 6 | [ 0 110 366 366] processing patch 7 | [ 55 0 366 366] processing patch 8 | [ 18 183 329 329] processing patch 9 | [ 73 183 329 329] processing patch 10 | [128 183 329 329] processing patch 11 | [183 128 329 329] processing patch 12 | [183 183 329 329] processing patch 13 | [ 0 0 256 256] processing patch 14 | [ 0 55 256 256] processing patch 15 | [ 0 110 256 256] processing patch 16 | [ 0 165 256 256] processing patch 17 | [ 0 219 256 256] processing patch 18 | [ 55 0 256 256] processing patch 19 | [110 0 256 256] processing patch 20 | [ 18 293 219 219] processing patch 21 | [ 73 293 219 219] processing patch 22 | [128 293 219 219] processing patch 23 | [183 293 219 219] processing patch 24 | [238 293 219 219] processing patch 25 | [293 183 219 219] processing patch 26 | [293 238 219 219] processing patch 27 | [323 323 158 158] processing patch 28 | [ 0 110 146 146] processing patch 29 | [ 0 165 146 146] processing patch 30 | [ 0 219 146 146] processing patch 31 | [ 0 274 146 146] processing patch 32 | [110 0 146 146] processing patch 33 | [165 0 146 146] finished Start Running 3D_Photo ... Loading edge model at 1676067019.1191473 Loading depth model at 1676067021.3657682 Loading rgb model at 1676067022.2461312 Writing depth ply (and basically doing everything) at 1676067023.0791702 writing Writing mesh file mesh/image.ply ... Making video at 1676067164.620918 fov: 53.13010235415598 Moviepy - Building video video/image_dolly-zoom-in.mp4. 0%| | 0/1 [04:41<?, ?it/s] Moviepy - Writing video video/image_dolly-zoom-in.mp4 0%| | 0/1 [04:41<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 2%|▎ | 3/120 [00:00<00:04, 23.96it/s, now=None] t: 28%|██▊ | 33/120 [00:00<00:00, 170.09it/s, now=None] t: 43%|████▎ | 52/120 [00:00<00:00, 172.39it/s, now=None] t: 59%|█████▉ | 71/120 [00:00<00:00, 174.31it/s, now=None] t: 74%|███████▍ | 89/120 [00:00<00:00, 171.63it/s, now=None] t: 89%|████████▉ | 107/120 [00:00<00:00, 172.74it/s, now=None] Moviepy - Done ! 0%| | 0/1 [04:43<?, ?it/s] Moviepy - video ready video/image_dolly-zoom-in.mp4 0%| | 0/1 [04:43<?, ?it/s] Moviepy - Building video video/image_zoom-in.mp4. 0%| | 0/1 [06:03<?, ?it/s] Moviepy - Writing video video/image_zoom-in.mp4 0%| | 0/1 [06:03<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 22%|██▎ | 27/120 [00:00<00:00, 266.32it/s, now=None] t: 45%|████▌ | 54/120 [00:00<00:00, 179.66it/s, now=None] t: 62%|██████▏ | 74/120 [00:00<00:00, 178.36it/s, now=None] t: 78%|███████▊ | 93/120 [00:00<00:00, 179.47it/s, now=None] t: 93%|█████████▎| 112/120 [00:00<00:00, 161.27it/s, now=None] Moviepy - Done ! 0%| | 0/1 [06:04<?, ?it/s] Moviepy - video ready video/image_zoom-in.mp4 0%| | 0/1 [06:04<?, ?it/s] Moviepy - Building video video/image_circle.mp4. 0%| | 0/1 [07:28<?, ?it/s] Moviepy - Writing video video/image_circle.mp4 0%| | 0/1 [07:28<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 24%|██▍ | 29/120 [00:00<00:00, 285.58it/s, now=None] t: 48%|████▊ | 58/120 [00:00<00:00, 186.34it/s, now=None] t: 66%|██████▌ | 79/120 [00:00<00:00, 177.51it/s, now=None] t: 82%|████████▏ | 98/120 [00:00<00:00, 165.16it/s, now=None] t: 97%|█████████▋| 116/120 [00:00<00:00, 155.31it/s, now=None] Moviepy - Done ! 0%| | 0/1 [07:30<?, ?it/s] Moviepy - video ready video/image_circle.mp4 0%| | 0/1 [07:30<?, ?it/s] Moviepy - Building video video/image_swing.mp4. 0%| | 0/1 [08:54<?, ?it/s] Moviepy - Writing video video/image_swing.mp4 0%| | 0/1 [08:54<?, ?it/s] t: 0%| | 0/120 [00:00<?, ?it/s, now=None] t: 24%|██▍ | 29/120 [00:00<00:00, 283.42it/s, now=None] t: 48%|████▊ | 58/120 [00:00<00:00, 196.96it/s, now=None] t: 67%|██████▋ | 80/120 [00:00<00:00, 183.06it/s, now=None] t: 83%|████████▎ | 100/120 [00:00<00:00, 174.52it/s, now=None] t: 98%|█████████▊| 118/120 [00:00<00:00, 166.56it/s, now=None] Moviepy - Done ! 0%| | 0/1 [08:56<?, ?it/s] Moviepy - video ready video/image_swing.mp4 0%| | 0/1 [08:56<?, ?it/s] 100%|██████████| 1/1 [08:56<00:00, 536.11s/it] 100%|██████████| 1/1 [08:56<00:00, 536.11s/it] total 1160 -rw-r--r-- 1 root root 356648 Feb 10 22:16 image_circle.mp4 -rw-r--r-- 1 root root 244326 Feb 10 22:14 image_dolly-zoom-in.mp4 -rw-r--r-- 1 root root 321436 Feb 10 22:18 image_swing.mp4 -rw-r--r-- 1 root root 255991 Feb 10 22:15 image_zoom-in.mp4
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