├── .gitignore ├── README.md ├── assets ├── cowmesh.png ├── medium.png ├── medium_4.png ├── rooster_blender.png └── rooster_rendered.png ├── data ├── capsule │ ├── capsule.mtl │ ├── capsule.obj │ └── capsule0.jpg ├── cow_mesh │ ├── cow.mtl │ ├── cow.obj │ └── cow_texture.png └── rooster │ ├── interface.png │ ├── render_rooster.png │ ├── rooster_1.0.1.3ds │ ├── rooster_1.0.1.blend │ ├── rooster_1.0.1.dae │ ├── rooster_1.0.1.fbx │ ├── rooster_1.0.1.mtl │ ├── rooster_1.0.1.obj │ ├── rooster_1.0.1.stl │ ├── rooster_1.0.1_copy.obj │ └── texture_rooster.png ├── environment.yml ├── out ├── capsule_elev0_azim0.png ├── capsule_elev0_azim180.png ├── capsule_elev0_azim270.png ├── capsule_elev0_azim60.png ├── capsule_elev0_azim90.png ├── capsule_elev180_azim0.png ├── capsule_elev180_azim180.png ├── capsule_elev180_azim270.png ├── capsule_elev180_azim60.png ├── capsule_elev180_azim90.png ├── capsule_elev90_azim0.png ├── capsule_elev90_azim180.png ├── capsule_elev90_azim270.png ├── capsule_elev90_azim60.png ├── capsule_elev90_azim90.png ├── cow_elev0_azim0.png ├── cow_elev0_azim180.png ├── cow_elev0_azim270.png ├── cow_elev0_azim60.png ├── cow_elev0_azim90.png ├── cow_elev180_azim0.png ├── cow_elev180_azim180.png ├── cow_elev180_azim270.png ├── cow_elev180_azim60.png ├── cow_elev180_azim90.png ├── cow_elev90_azim0.png ├── cow_elev90_azim180.png ├── cow_elev90_azim270.png ├── cow_elev90_azim60.png ├── cow_elev90_azim90.png ├── rooster_1_elev0_azim0.png ├── rooster_1_elev0_azim180.png ├── rooster_1_elev0_azim270.png ├── rooster_1_elev0_azim60.png ├── rooster_1_elev0_azim90.png ├── rooster_1_elev180_azim0.png ├── rooster_1_elev180_azim180.png ├── rooster_1_elev180_azim270.png ├── rooster_1_elev180_azim60.png ├── rooster_1_elev180_azim90.png ├── rooster_1_elev90_azim0.png ├── rooster_1_elev90_azim180.png ├── rooster_1_elev90_azim270.png ├── rooster_1_elev90_azim60.png └── rooster_1_elev90_azim90.png ├── params.json ├── params_demo.json ├── process_rooster_mesh.py ├── render.py ├── render_demo.ipynb └── utils.py /.gitignore: -------------------------------------------------------------------------------- 1 | __pycache__ 2 | cub-1.10.0 3 | .ipynb_checkpoints 4 | # MacOS 5 | .DS_Store 6 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Medium article 2 | 3 | [Checkout](https://adelekuzmiakova.medium.com/how-to-render-3d-files-using-pytorch3d-ef9de72483f8?source=friends_link&sk=d89816e7e6f338dfc68da836757e149d) the Medium walkthrough 👋 on how to render 3D `.obj` meshes from various viewpoints to create 2D images. 4 | 5 | ![Alt text](assets/medium.png?raw=true "Title") 6 | 7 | [Read more](https://adelekuzmiakova.medium.com/how-to-render-3d-files-using-pytorch3d-ef9de72483f8?source=friends_link&sk=d89816e7e6f338dfc68da836757e149d) 8 | 9 | ## Setup your environment 10 | 11 | ```bash 12 | conda env create -f environment.yml # creates pytorch3d-renderer environment 13 | conda activate pytorch3d-renderer # activates the environment 14 | conda deactivate # deactivates the environment 15 | ``` 16 | 17 | 18 | 19 | 20 | ## Try out the demo 21 | 22 | `render_demo.ipynb` is a Jupyter notebook that walks you through the entire rendering pipeline in PyTorch. The rendering parameters are specified in `params_demo.json` and can be modified there. 23 | 24 | ## Rendering code 25 | 26 | The actual code is written in `render.py`: 27 | 28 | ```bash 29 | python -m render 30 | ``` 31 | 32 | This takes a 3D `.obj` file and renders it to create 2D images from multiple viewpoints based on parameters specified in `params.json`. The resulting images are then saved in `out/` directory. The `.json` parameters include: 33 | 34 | `image_size` is a size of an actual 2D output image. The smaller the size, the more pixelated the image will appear. Try 512 or 1024 to get crisp images but, by the same token, the code will take longer to run.\ 35 | `camera_dist` refers to the distance between the camera and the object.\ 36 | `elevation` is a **list** of elevation values and basically tell us from how high we are looking at the object. **Elevation refers to the angle between the vector from the object to the camera and the horizontal plane y=0 (plane xz).**\ 37 | `azim_angle` is a **list** of azimuth angle values and basically tell us from which side (e.g. left size, right side, front view, back view, etc.) we are looking at the object. What's azimuth angle? **Let's say you have a vector from the object to the camera and you project it onto a horizontal plane y=0. The azimuth angle is then the angle between the projected vector and a reference vector at (0,0,1) on the reference plane (horizontal plane).** [Checkout](https://www.celestis.com/resources/faq/what-are-the-azimuth-and-elevation-of-a-satellite/) this illustration.\ 38 | `obj_filename` is a path to the `.obj` file you want to render. 39 | 40 |   41 | 42 | ### a) 3D cow mesh example 43 | 44 | 45 | `.json` parameters: 46 | 47 | ```json 48 | { 49 | "image_size": 256, 50 | "camera_dist": 3, 51 | "elevation": [0, 90, 180], 52 | "azim_angle": [0, 60, 90, 180, 270], 53 | "obj_filename": "data/cow_mesh/cow.obj" 54 | } 55 | ``` 56 | 57 |   58 | 59 | Rendered results (also stored in `out` directory): 60 | ![Alt text](assets/cowmesh.png?raw=true "Title") 61 | 62 |   63 | 64 | ### b) 3D capsule mesh example 65 | 66 | [Data source](http://paulbourke.net/dataformats/obj/minobj.html) 67 | 68 | `.json` parameters: 69 | 70 | ```json 71 | { 72 | "image_size": 256, 73 | "camera_dist": 3, 74 | "elevation": [0, 90, 180], 75 | "azim_angle": [0, 60, 90, 180, 270], 76 | "obj_filename": "data/capsule/capsule.obj" 77 | } 78 | ``` 79 | 80 | ### c) 2D rooster mesh example 81 | 82 | [Data source](https://free3d.com/3d-model/low-poly-rooster-31363.html) 83 | 84 | **IMPORTANT:** Pre-process the mesh to make sure that 1 of the 3 coordinates (x, y, or z) is a constant. In this case, `process_rooster_mesh.py` sets the z-coordinate to 0. 85 | 86 | ```bash 87 | python -m process_rooster_mesh 88 | ``` 89 | 90 | 91 | `.json` parameters: 92 | 93 | ```json 94 | { 95 | "image_size": 1024, 96 | "camera_dist": 10, 97 | "elevation": [0, 90, 180], 98 | "azim_angle": [0, 60, 90, 180, 270], 99 | "obj_filename": "data/rooster/rooster_1.0.1.obj" 100 | } 101 | ``` 102 | Blender visualization: 103 | ![Alt text](assets/rooster_blender.png?raw=true "Title") 104 | 105 | 106 | Rendered results (also stored in `out` directory): 107 | ![Alt text](assets/rooster_rendered.png?raw=true "Title") 108 | -------------------------------------------------------------------------------- /assets/cowmesh.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adele-k02/pytorch3d-renderer/14448d119bcbef7c44f68565599817b687d982b2/assets/cowmesh.png 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/data/rooster/rooster_1.0.1.blend: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/adele-k02/pytorch3d-renderer/14448d119bcbef7c44f68565599817b687d982b2/data/rooster/rooster_1.0.1.blend -------------------------------------------------------------------------------- /data/rooster/rooster_1.0.1.dae: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | Blender User 6 | Blender 2.77.0 commit date:2016-04-05, commit time:18:12, hash:abf6f08 7 | 8 | 2016-06-21T10:52:00 9 | 2016-06-21T10:52:00 10 | 11 | Z_UP 12 | 13 | 14 | 15 | 16 | 17 | 18 | 49.13434 19 | 1 20 | 0.1 21 | 100 22 | 23 | 24 | 25 | 26 | 27 | 0 28 | 0 29 | 0 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 1 1 1 39 | 1 40 | 0 41 | 0.00111109 42 | 43 | 44 | 45 | 46 | 0.000999987 47 | 1 48 | 0.1 49 | 0.1 50 | 1 51 | 1 52 | 1 53 | 2 54 | 0 55 | 1 56 | 1 57 | 1 58 | 1 59 | 1 60 | 0 61 | 2880 62 | 2 63 | 30.002 64 | 1.000799 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| vt 0.0980 0.7424 313 | vt 0.2802 0.7738 314 | vt 0.3102 0.8219 315 | vt 0.2062 0.8192 316 | vt 0.2192 0.7747 317 | vt 0.4490 0.7420 318 | vt 0.4538 0.7676 319 | vt 0.1453 0.2974 320 | vt 0.1261 0.3835 321 | vt 0.0511 0.3798 322 | vt 0.0514 0.3384 323 | vt 0.2341 0.3063 324 | vt 0.2138 0.3794 325 | vt 0.1366 0.7393 326 | vt 0.0750 0.7163 327 | vt 0.0932 0.6961 328 | vt 0.1580 0.7067 329 | vt 0.2235 0.7528 330 | vt 0.2231 0.7106 331 | vt 0.0573 0.4172 332 | vt 0.1180 0.3957 333 | vt 0.1217 0.4615 334 | vt 0.0808 0.4562 335 | vt 0.2257 0.4154 336 | vt 0.2108 0.4648 337 | vt 0.2717 0.0710 338 | vt 0.2768 0.0857 339 | vt 0.2688 0.0962 340 | vt 0.2563 0.0973 341 | vt 0.2359 0.0831 342 | vt 0.2352 0.0372 343 | vt 0.2054 0.0469 344 | vt 0.2274 0.0890 345 | vt 0.1950 0.0503 346 | vt 0.1905 0.1035 347 | vt 0.1660 0.0597 348 | vt 0.2408 0.1111 349 | vt 0.2357 0.1247 350 | vt 0.2184 0.1270 351 | vt 0.1774 0.1035 352 | vt 0.1492 0.0652 353 | vt 0.1448 0.1190 354 | vt 0.1225 0.0761 355 | vt 0.1927 0.1451 356 | vt 0.1838 0.1560 357 | vt 0.1675 0.1555 358 | vt 0.1249 0.1175 359 | vt 0.1089 0.0694 360 | vt 0.0905 0.1126 361 | vt 0.0763 0.0536 362 | vt 0.1353 0.1590 363 | vt 0.1242 0.1706 364 | vt 0.1102 0.1643 365 | vt 0.0787 0.1131 366 | vt 0.0530 0.0422 367 | vt 0.0453 0.1094 368 | vt 0.0317 0.0319 369 | vt 0.0917 0.1669 370 | vt 0.0779 0.1708 371 | vt 0.0651 0.1645 372 | vt 0.3173 0.7100 373 | vt 0.2978 0.7521 374 | vt 0.4183 0.7023 375 | vt 0.3969 0.7349 376 | vt 0.4453 0.9672 377 | vt 0.4253 0.9030 378 | vt 0.5411 0.8640 379 | vt 0.5611 0.9235 380 | vt 0.0746 0.9366 381 | vt 0.0279 0.8634 382 | vt 0.1787 0.9276 383 | vt 0.1891 0.9777 384 | vt 0.3259 0.9380 385 | vt 0.3580 0.9846 386 | vt 0.5902 0.0836 387 | vt 0.5746 0.0795 388 | vt 0.5729 0.0561 389 | vt 0.5885 0.0602 390 | vt 0.5551 0.0831 391 | vt 0.5535 0.0597 392 | vt 0.6823 0.0503 393 | vt 0.6804 0.0384 394 | vt 0.6912 0.0344 395 | vt 0.5728 0.0306 396 | vt 0.5533 0.0342 397 | vt 0.5582 0.0176 398 | vt 0.5696 0.0155 399 | vt 0.4716 0.0526 400 | vt 0.4724 0.0642 401 | vt 0.4578 0.0470 402 | vt 0.6479 0.0483 403 | vt 0.6515 0.0677 404 | vt 0.5095 0.0748 405 | vt 0.5078 0.0514 406 | vt 0.5898 0.1329 407 | vt 0.5728 0.1316 408 | vt 0.5533 0.1352 409 | vt 0.5246 0.1363 410 | vt 0.5241 0.1494 411 | vt 0.5068 0.1379 412 | vt 0.5070 0.1318 413 | vt 0.6745 0.0531 414 | vt 0.6722 0.0382 415 | vt 0.6804 0.0384 416 | vt 0.6823 0.0503 417 | vt 0.0591 0.2110 418 | vt 0.1020 0.2054 419 | vt 0.1336 0.2594 420 | vt 0.0908 0.2650 421 | vt 0.1932 0.1849 422 | vt 0.2249 0.2389 423 | vt 0.6722 0.0382 424 | vt 0.6745 0.0531 425 | vt 0.4833 0.0499 426 | vt 0.4844 0.0652 427 | vt 0.3194 0.0300 428 | vt 0.3402 0.0416 429 | vt 0.3440 0.0648 430 | vt 0.2909 0.0532 431 | vt 0.2938 0.0348 432 | vt 0.2890 0.0821 433 | vt 0.3474 0.0899 434 | vt 0.3831 0.0338 435 | vt 0.4039 0.0454 436 | vt 0.4078 0.0686 437 | vt 0.3546 0.0570 438 | vt 0.3575 0.0387 439 | vt 0.4058 0.0976 440 | vt 0.4058 0.1208 441 | vt 0.3474 0.1130 442 | vt 0.2890 0.1053 443 | vt 0.4833 0.0499 444 | vt 0.4844 0.0652 445 | vt 0.4724 0.0642 446 | vt 0.4716 0.0526 447 | vt 0.6515 0.0677 448 | vt 0.6479 0.0483 449 | vt 0.5246 0.1363 450 | vt 0.5241 0.1494 451 | vt 0.5068 0.1379 452 | vt 0.5070 0.1318 453 | vt 0.5902 0.0836 454 | vt 0.5898 0.1329 455 | vt 0.5728 0.1316 456 | vt 0.5746 0.0795 457 | vt 0.5533 0.1352 458 | vt 0.5551 0.0831 459 | vt 0.5722 0.1494 460 | vt 0.5527 0.1530 461 | vt 0.5897 0.1496 462 | vt 0.5729 0.0561 463 | vt 0.5535 0.0597 464 | vt 0.5533 0.0342 465 | vt 0.5728 0.0306 466 | vt 0.5095 0.0748 467 | vt 0.5078 0.0514 468 | vt 0.5885 0.0602 469 | vt 0.4578 0.0470 470 | vt 0.5582 0.0176 471 | vt 0.5696 0.0155 472 | vt 0.6912 0.0344 473 | vt 0.5503 0.2229 474 | vt 0.5698 0.2193 475 | vt 0.5842 0.3633 476 | vt 0.5143 0.3597 477 | vt 0.5893 0.2156 478 | vt 0.6541 0.3669 479 | vt 0.9122 0.2056 480 | vt 0.8945 0.1769 481 | vt 0.9236 0.1588 482 | vt 0.9316 0.1612 483 | vt 0.8928 0.1749 484 | vt 0.8628 0.1636 485 | vt 0.9151 0.1569 486 | vt 0.9193 0.1600 487 | vt 0.7796 0.1994 488 | vt 0.7490 0.1593 489 | vt 0.8175 0.1657 490 | vt 0.8472 0.1897 491 | vt 0.7781 0.2536 492 | vt 0.8524 0.1910 493 | vt 0.8592 0.2344 494 | vn -0.0000 0.0000 1.0000 495 | usemtl Material 496 | s off 497 | f 14/1/1 6/2/1 10/3/1 16/4/1 498 | f 13/5/1 5/6/1 6/2/1 14/1/1 499 | f 3/7/1 12/8/1 15/9/1 500 | f 228/10/1 13/5/1 208/11/1 227/12/1 501 | f 16/4/1 10/3/1 1/13/1 12/8/1 502 | f 12/8/1 21/14/1 8/15/1 15/9/1 503 | f 9/16/1 16/4/1 12/8/1 3/7/1 504 | f 163/17/1 5/6/1 13/5/1 228/10/1 505 | f 208/11/1 13/5/1 14/1/1 4/18/1 506 | f 4/18/1 14/1/1 16/4/1 9/16/1 507 | f 21/14/1 7/19/1 17/20/1 23/21/1 508 | f 24/22/1 33/23/1 19/24/1 509 | f 28/25/1 29/26/1 24/22/1 20/27/1 510 | f 8/15/1 21/14/1 23/21/1 18/28/1 511 | f 12/8/1 1/13/1 7/19/1 21/14/1 512 | f 24/22/1 19/24/1 30/29/1 513 | f 20/27/1 24/22/1 26/30/1 25/31/1 514 | f 18/28/1 23/21/1 29/26/1 28/25/1 515 | f 23/21/1 17/20/1 27/32/1 29/26/1 516 | f 24/22/1 30/29/1 22/33/1 26/30/1 517 | f 29/26/1 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-------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | # coding: utf-8 3 | 4 | import json 5 | from utils import Params 6 | 7 | 8 | def create_2d_mesh(orig_filename, new_filename, z_coord): 9 | """ 10 | Creates a new obj file by copying the contents from the original obj file and 11 | replacing the z-coordinate values with a constant (0 in this case). 12 | 13 | Args: 14 | orig_filename: str, path to the original obj filename 15 | new_filename: str, path to the new obj filename 16 | z_coord: list, new z-coordinate which will replace old z-values 17 | """ 18 | with open(orig_filename) as orig_file, open(new_filename, 'w') as new_file: 19 | # Read through lines in the original obj file 20 | for line in orig_file: 21 | # Look for vertex coordinates: do not match "vt" or "vn" 22 | if 'v' == line[0] and line[1].isspace(): 23 | partial_coord = line.split(' ')[0:-1] 24 | # Use previous x- and y-coordinates and append the new z-coordinate 25 | line = partial_coord + z_coord 26 | line = ' '.join([str(elem) for elem in line]) 27 | new_file.write(str(line) + '\n') 28 | else: 29 | new_file.write(str(line)) 30 | orig_file.close() 31 | new_file.close() 32 | 33 | 34 | def main(): 35 | orig_filename = "data/rooster/rooster_1.0.1.obj" 36 | added_string = "_copy.obj" 37 | # Generate a new obj filename 38 | new_filename = orig_filename.split('.obj')[0] + added_string 39 | params = Params("params.json") 40 | z_coord = [params.z_coord] 41 | create_2d_mesh(orig_filename, new_filename, z_coord) 42 | print("Done. Created a new mesh " + str(new_filename)) 43 | 44 | 45 | if __name__ == "__main__": 46 | main() 47 | -------------------------------------------------------------------------------- /render.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | # coding: utf-8 3 | 4 | import os 5 | import sys 6 | import torch 7 | import numpy as np 8 | import json 9 | if torch.__version__ == '1.6.0+cu101' and sys.platform.startswith('linux'): 10 | get_ipython().system('pip install pytorch3d') 11 | else: 12 | need_pytorch3d = False 13 | try: 14 | import pytorch3d 15 | except ModuleNotFoundError: 16 | need_pytorch3d = True 17 | if need_pytorch3d: 18 | get_ipython().system('curl -LO https://github.com/NVIDIA/cub/archive/1.10.0.tar.gz') 19 | get_ipython().system('tar xzf 1.10.0.tar.gz') 20 | os.environ["CUB_HOME"] = os.getcwd() + "/cub-1.10.0" 21 | get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") 22 | from pytorch3d.io import load_obj 23 | from pytorch3d.structures import Meshes 24 | from pytorch3d.renderer import ( 25 | look_at_view_transform, 26 | FoVPerspectiveCameras, 27 | FoVOrthographicCameras, 28 | Materials, 29 | RasterizationSettings, 30 | MeshRenderer, 31 | MeshRasterizer, 32 | SoftPhongShader, 33 | TexturesVertex, 34 | TexturesAtlas, 35 | PointsRenderer, 36 | PointsRasterizationSettings, 37 | PointsRasterizer 38 | ) 39 | import matplotlib.pyplot as plt 40 | import matplotlib 41 | from utils import Params 42 | 43 | 44 | # Set the device 45 | if torch.cuda.is_available(): 46 | device = torch.device("cuda:0") 47 | torch.cuda.set_device(device) 48 | else: 49 | device = torch.device("cpu") 50 | 51 | # Import parameters 52 | params = Params("params.json") 53 | obj_filename = params.obj_filename 54 | 55 | 56 | def get_mesh(obj_filename, device): 57 | """ 58 | Generates Meshes object and initializes the mesh with vertices, faces, 59 | and textures. 60 | 61 | Args: 62 | obj_filename: str, path to the 3D obj filename 63 | device: str, the torch device containing a device type ('cpu' or 64 | 'cuda') 65 | 66 | Returns: 67 | mesh: Meshes object 68 | """ 69 | # Get vertices, faces, and auxiliary information 70 | verts, faces, aux = load_obj( 71 | obj_filename, 72 | device=device, 73 | load_textures=True, 74 | create_texture_atlas=True, 75 | texture_atlas_size=4, 76 | texture_wrap="repeat" 77 | ) 78 | # Create a textures object 79 | atlas = aux.texture_atlas 80 | # Create Meshes object 81 | mesh = Meshes( 82 | verts=[verts], 83 | faces=[faces.verts_idx], 84 | textures=TexturesAtlas(atlas=[atlas]),) 85 | return mesh 86 | 87 | 88 | def get_renderer(image_size, dist, device, elev, azim): 89 | """ 90 | Generates a mesh renderer by combining a rasterizer and a shader. 91 | 92 | Args: 93 | image_size: int, the size of the rendered .png image 94 | dist: int, distance between the camera and 3D object 95 | device: str, the torch device containing a device type ('cpu' or 96 | 'cuda') 97 | elev: list, contains elevation values 98 | azim: list, contains azimuth angle values 99 | 100 | Returns: 101 | renderer: MeshRenderer class 102 | """ 103 | # Initialize the camera with camera distance, elevation, azimuth angle, 104 | # and image size 105 | R, T = look_at_view_transform(dist=dist, elev=elev, azim=azim) 106 | cameras = FoVPerspectiveCameras(device=device, R=R, T=T) 107 | raster_settings = RasterizationSettings( 108 | image_size=image_size, 109 | blur_radius=0.0, 110 | faces_per_pixel=1, 111 | ) 112 | # Initialize rasterizer by using a MeshRasterizer class 113 | rasterizer = MeshRasterizer( 114 | cameras=cameras, 115 | raster_settings=raster_settings 116 | ) 117 | # The textured phong shader interpolates the texture uv coordinates for 118 | # each vertex, and samples from a texture image. 119 | shader = SoftPhongShader(device=device, cameras=cameras) 120 | # Create a mesh renderer by composing a rasterizer and a shader 121 | renderer = MeshRenderer(rasterizer, shader) 122 | return renderer 123 | 124 | 125 | def render_image(renderer, mesh, obj_filename, azim, elev): 126 | """ 127 | Renders an image using MeshRenderer class and Meshes object. Saves the 128 | rendered image as a .png file. 129 | 130 | Args: 131 | image_size: int, the size of the rendered .png image 132 | dist: int, distance between the camera and 3D object 133 | device: str, the torch device containing a device type ('cpu' or 134 | 'cuda') 135 | elev: list, contains elevation values 136 | azim: list, contains azimuth angle values 137 | 138 | Returns: 139 | renderer: MeshRenderer class 140 | """ 141 | image = renderer(mesh) 142 | dir_to_save = "out" 143 | os.makedirs(dir_to_save, exist_ok=True) 144 | out = os.path.normpath(obj_filename).split(os.path.sep) 145 | mesh_filename = out[-1].split(".")[0] 146 | sep = '_' 147 | file_to_save = '{0}{1}{2}{3}{4}{5}{6}{7}'.format(mesh_filename, sep, 148 | "elev", int(elev), 149 | sep, "azim", 150 | int(azim), ".png") 151 | filename = os.path.join(dir_to_save, file_to_save) 152 | matplotlib.image.imsave(filename, image[0, ..., :3].cpu().numpy()) 153 | print("Saved image as " + str(filename)) 154 | 155 | 156 | def compile_all_steps(image_size, dist, device, elev, azim, obj_filename): 157 | """ 158 | Combines the above steps. 159 | 160 | Args: 161 | image_size: int, the size of the rendered .png image 162 | dist: int, distance between the camera and 3D object 163 | device: str, the torch device containing a device type ('cpu' or 164 | 'cuda') 165 | elev: list, contains elevation values 166 | azim: list, contains azimuth angle values 167 | obj_filename: str, path to the 3D obj filename 168 | 169 | Returns: 170 | None 171 | """ 172 | renderer = get_renderer(image_size, dist, device, elev, azim) 173 | mesh = get_mesh(obj_filename, device) 174 | render_image(renderer, mesh, obj_filename, azim, elev) 175 | return None 176 | 177 | 178 | def main(): 179 | [compile_all_steps(params.image_size, params.camera_dist, device, x, y, 180 | params.obj_filename) 181 | for x in params.elevation for y in params.azim_angle] 182 | 183 | 184 | if __name__ == "__main__": 185 | main() 186 | -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- 1 | import json 2 | import logging 3 | import os 4 | import shutil 5 | import matplotlib.pyplot as plt 6 | 7 | 8 | class Params(): 9 | """Class that loads hyperparameters from a json file. 10 | Example: 11 | ``` 12 | params = Params(json_path) 13 | print(params.learning_rate) 14 | params.learning_rate = 0.5 15 | ``` 16 | """ 17 | 18 | def __init__(self, json_path): 19 | with open(json_path) as f: 20 | params = json.load(f) 21 | self.__dict__.update(params) 22 | 23 | def save(self, json_path): 24 | with open(json_path, 'w') as f: 25 | json.dump(self.__dict__, f, indent=4) 26 | 27 | def update(self, json_path): 28 | """Loads parameters from json file""" 29 | with open(json_path) as f: 30 | params = json.load(f) 31 | self.__dict__.update(params) 32 | 33 | @property 34 | def dict(self): 35 | """Gives dict-like access to Params instance by params.dict['learning_rate']""" 36 | return self.__dict__ 37 | 38 | 39 | def image_grid( 40 | images, 41 | rows=None, 42 | cols=None, 43 | fill: bool = True, 44 | show_axes: bool = False, 45 | rgb: bool = True, 46 | ): 47 | """ 48 | A util function for plotting a grid of images. 49 | 50 | Args: 51 | images: (N, H, W, 4) array of RGBA images 52 | rows: number of rows in the grid 53 | cols: number of columns in the grid 54 | fill: boolean indicating if the space between images should be filled 55 | show_axes: boolean indicating if the axes of the plots should be visible 56 | rgb: boolean, If True, only RGB channels are plotted. 57 | If False, only the alpha channel is plotted. 58 | 59 | Returns: 60 | None 61 | """ 62 | if (rows is None) != (cols is None): 63 | raise ValueError("Specify either both rows and cols or neither.") 64 | 65 | if rows is None: 66 | rows = len(images) 67 | cols = 1 68 | 69 | gridspec_kw = {"wspace": 0.0, "hspace": 0.0} if fill else {} 70 | fig, axarr = plt.subplots(rows, cols, gridspec_kw=gridspec_kw, figsize=(15, 9)) 71 | bleed = 0 72 | fig.subplots_adjust(left=bleed, bottom=bleed, right=(1 - bleed), top=(1 - bleed)) 73 | 74 | for ax, im in zip(axarr.ravel(), images): 75 | if rgb: 76 | # only render RGB channels 77 | ax.imshow(im[..., :3]) 78 | else: 79 | # only render Alpha channel 80 | ax.imshow(im[..., 3]) 81 | if not show_axes: 82 | ax.set_axis_off() 83 | --------------------------------------------------------------------------------