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  1. anydoor/cldm/__pycache__/cldm.cpython-38.pyc +0 -0
  2. anydoor/cldm/__pycache__/ddim_hacked.cpython-38.pyc +0 -0
  3. anydoor/cldm/__pycache__/hack.cpython-38.pyc +0 -0
  4. anydoor/cldm/__pycache__/model.cpython-38.pyc +0 -0
  5. anydoor/datasets/__pycache__/data_utils.cpython-38.pyc +0 -0
  6. anydoor/dinov2/__pycache__/hubconf.cpython-38.pyc +0 -0
  7. anydoor/dinov2/dinov2/__pycache__/__init__.cpython-38.pyc +0 -0
  8. anydoor/dinov2/dinov2/layers/__pycache__/__init__.cpython-38.pyc +0 -0
  9. anydoor/dinov2/dinov2/layers/__pycache__/attention.cpython-38.pyc +0 -0
  10. anydoor/dinov2/dinov2/layers/__pycache__/block.cpython-38.pyc +0 -0
  11. anydoor/dinov2/dinov2/layers/__pycache__/dino_head.cpython-38.pyc +0 -0
  12. anydoor/dinov2/dinov2/layers/__pycache__/drop_path.cpython-38.pyc +0 -0
  13. anydoor/dinov2/dinov2/layers/__pycache__/layer_scale.cpython-38.pyc +0 -0
  14. anydoor/dinov2/dinov2/layers/__pycache__/mlp.cpython-38.pyc +0 -0
  15. anydoor/dinov2/dinov2/layers/__pycache__/patch_embed.cpython-38.pyc +0 -0
  16. anydoor/dinov2/dinov2/layers/__pycache__/swiglu_ffn.cpython-38.pyc +0 -0
  17. anydoor/dinov2/dinov2/models/__pycache__/__init__.cpython-38.pyc +0 -0
  18. anydoor/dinov2/dinov2/models/__pycache__/vision_transformer.cpython-38.pyc +0 -0
  19. anydoor/ldm/__pycache__/util.cpython-38.pyc +0 -0
  20. anydoor/ldm/models/__pycache__/autoencoder.cpython-38.pyc +0 -0
  21. anydoor/ldm/models/diffusion/__pycache__/__init__.cpython-38.pyc +0 -0
  22. anydoor/ldm/models/diffusion/__pycache__/ddim.cpython-38.pyc +0 -0
  23. anydoor/ldm/models/diffusion/__pycache__/ddpm.cpython-38.pyc +0 -0
  24. anydoor/ldm/modules/__pycache__/attention.cpython-38.pyc +0 -0
  25. anydoor/ldm/modules/__pycache__/ema.cpython-38.pyc +0 -0
  26. anydoor/ldm/modules/diffusionmodules/__pycache__/__init__.cpython-38.pyc +0 -0
  27. anydoor/ldm/modules/diffusionmodules/__pycache__/model.cpython-38.pyc +0 -0
  28. anydoor/ldm/modules/diffusionmodules/__pycache__/openaimodel.cpython-38.pyc +0 -0
  29. anydoor/ldm/modules/diffusionmodules/__pycache__/util.cpython-38.pyc +0 -0
  30. anydoor/ldm/modules/distributions/__pycache__/__init__.cpython-38.pyc +0 -0
  31. anydoor/ldm/modules/distributions/__pycache__/distributions.cpython-38.pyc +0 -0
  32. anydoor/ldm/modules/encoders/__pycache__/__init__.cpython-38.pyc +0 -0
  33. anydoor/ldm/modules/encoders/__pycache__/modules.cpython-38.pyc +0 -0
  34. anydoor/run_inference_train_x.py +36 -31
  35. adbase-step=44375.ckpt → pink_girl/image-mask/bottom_jean.png +2 -2
  36. pink_girl/image-mask/bra_model_768.png +3 -0
  37. pink_girl/image/bottom_jean.jpg +0 -0
  38. pink_girl/image/bra_model_768.jpg +0 -0
  39. pink_girl/out_bot/bottom_z_40195438_0129_1.jpg +0 -0
  40. pink_girl/out_bot/bottom_z_40414461_0839_1.jpg +0 -0
  41. pink_girl/out_bot/bottom_z_40903231_0788_1.jpg +0 -0
  42. pink_girl/out_bot/bottom_z_40947839_0430_1.jpg +0 -0
  43. pink_girl/out_bot/bottom_z_40947839_0907_1.jpg +0 -0
  44. pink_girl/out_bot/bottom_z_40955124_0888_1.jpg +0 -0
  45. pink_girl/out_bot/bottom_z_40979991_0565_1.jpg +0 -0
  46. pink_girl/out_bot/bottom_z_41227558_0060_1.jpg +0 -0
  47. pink_girl/out_bot/bottom_z_41227558_0484_1.jpg +0 -0
  48. pink_girl/out_bot/bottom_z_41612835_0416_1.jpg +0 -0
  49. pink_girl/out_bot/bottom_z_42331247_0430_1.jpg +0 -0
  50. pink_girl/out_bot/bottom_z_42331568_0409_1.jpg +0 -0
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anydoor/run_inference_train_x.py CHANGED
@@ -240,57 +240,62 @@ if __name__ == '__main__':
240
 
241
  # Assuming 'inference_single_image' function is defined elsewhere
242
 
243
- save_dir = '/work/pink_girl/out'
244
  cloth_dir = '/work/pink_girl/cloth/top'
245
  cloth_mask_dir = '/work/pink_girl/cloth-mask'
246
  image_dir = '/work/pink_girl/image'
247
  image_parse_v3_dir = '/work/pink_girl/image-mask'
248
-
249
  # Fixed reference image and its mask
250
- fixed_ref_image_name = 'we_picked_8.jpg'
251
  fixed_ref_image_path = os.path.join(image_dir, fixed_ref_image_name)
252
- fixed_ref_mask_path = os.path.join(image_parse_v3_dir, 'T_we_picked_8.png')
 
 
 
 
 
253
 
254
  # Ensure the save directory exists
255
  if not os.path.exists(save_dir):
256
  os.makedirs(save_dir)
257
 
258
- # Create list of cloth image names
259
- cloth_image_names = os.listdir(cloth_dir)[:40]
260
 
261
- # First loop for the top half
262
- for cloth_image_name in cloth_image_names:
263
- cloth_image_path = os.path.join(cloth_dir, cloth_image_name)
264
- cloth_mask_path = os.path.join(cloth_mask_dir, cloth_image_name)
265
 
266
- cloth_image = cv2.imread(cloth_image_path)
267
- cloth_image = cv2.cvtColor(cloth_image, cv2.COLOR_BGR2RGB)
268
- cloth_mask = (cv2.imread(cloth_mask_path) > 128).astype(np.uint8)[:, :, 0]
269
 
270
- ref_image = cv2.imread(fixed_ref_image_path)
271
- ref_image = cv2.cvtColor(ref_image, cv2.COLOR_BGR2RGB)
272
- ref_mask = Image.open(fixed_ref_mask_path).convert('P')
273
- ref_mask = np.array(ref_mask) == 1
274
 
275
- gen_image = inference_single_image(cloth_image, cloth_mask, ref_image, ref_mask)
276
- gen_path = os.path.join(save_dir, 'gen_top_' + cloth_image_name)
277
- single_path = os.path.join(save_dir, 'single_top_' + cloth_image_name)
278
- clothe_path = os.path.join(save_dir, 'single_cloth_top_' + cloth_image_name)
279
 
280
- vis_image = cv2.hconcat([cloth_image, ref_image, gen_image])
281
- cv2.imwrite(gen_path, cv2.cvtColor(vis_image, cv2.COLOR_RGB2BGR))
282
- cv2.imwrite(clothe_path, cv2.cvtColor(cloth_image, cv2.COLOR_RGB2BGR))
283
- cv2.imwrite(single_path, cv2.cvtColor(gen_image, cv2.COLOR_RGB2BGR))
284
- top_image_path = os.path.join(save_dir, 'top_z_' + cloth_image_name)
285
- top_half_cropped = resize_and_crop(gen_image, 512, 600, True, False)
286
- cv2.imwrite(top_image_path, cv2.cvtColor(top_half_cropped, cv2.COLOR_RGB2BGR))
287
 
288
 
289
 
290
- # Update the cloth directory and mask path for the bottom half processing
291
  cloth_dir1 = '/work/pink_girl/cloth/trou'
292
- fixed_ref_mask_path = os.path.join(image_parse_v3_dir, 'trou1.png')
293
- cloth_image_names = os.listdir(cloth_dir1)[:40]
294
 
295
  # Second loop for the bottom half
296
  for cloth_image_name in cloth_image_names:
 
240
 
241
  # Assuming 'inference_single_image' function is defined elsewhere
242
 
243
+ save_dir = '/work/pink_girl/out_bot'
244
  cloth_dir = '/work/pink_girl/cloth/top'
245
  cloth_mask_dir = '/work/pink_girl/cloth-mask'
246
  image_dir = '/work/pink_girl/image'
247
  image_parse_v3_dir = '/work/pink_girl/image-mask'
248
+
249
  # Fixed reference image and its mask
250
+ fixed_ref_image_name = 'bottom_jean.jpg'
251
  fixed_ref_image_path = os.path.join(image_dir, fixed_ref_image_name)
252
+ fixed_ref_mask_path = os.path.join(image_parse_v3_dir, 'bottom_jean.png')
253
+
254
+ # # Fixed reference image and its mask
255
+ # fixed_ref_image_name = 'bra_model_768.jpg'
256
+ # fixed_ref_image_path = os.path.join(image_dir, fixed_ref_image_name)
257
+ # fixed_ref_mask_path = os.path.join(image_parse_v3_dir, 'bra_model_768.png')
258
 
259
  # Ensure the save directory exists
260
  if not os.path.exists(save_dir):
261
  os.makedirs(save_dir)
262
 
263
+ # # Create list of cloth image names
264
+ # cloth_image_names = os.listdir(cloth_dir)[:40]
265
 
266
+ # # First loop for the top half
267
+ # for cloth_image_name in cloth_image_names:
268
+ # cloth_image_path = os.path.join(cloth_dir, cloth_image_name)
269
+ # cloth_mask_path = os.path.join(cloth_mask_dir, cloth_image_name)
270
 
271
+ # cloth_image = cv2.imread(cloth_image_path)
272
+ # cloth_image = cv2.cvtColor(cloth_image, cv2.COLOR_BGR2RGB)
273
+ # cloth_mask = (cv2.imread(cloth_mask_path) > 128).astype(np.uint8)[:, :, 0]
274
 
275
+ # ref_image = cv2.imread(fixed_ref_image_path)
276
+ # ref_image = cv2.cvtColor(ref_image, cv2.COLOR_BGR2RGB)
277
+ # ref_mask = Image.open(fixed_ref_mask_path).convert('P')
278
+ # ref_mask = np.array(ref_mask) == 1
279
 
280
+ # gen_image = inference_single_image(cloth_image, cloth_mask, ref_image, ref_mask)
281
+ # gen_path = os.path.join(save_dir, 'gen_top_' + cloth_image_name)
282
+ # single_path = os.path.join(save_dir, 'single_top_' + cloth_image_name)
283
+ # clothe_path = os.path.join(save_dir, 'single_cloth_top_' + cloth_image_name)
284
 
285
+ # vis_image = cv2.hconcat([cloth_image, ref_image, gen_image])
286
+ # cv2.imwrite(gen_path, cv2.cvtColor(vis_image, cv2.COLOR_RGB2BGR))
287
+ # cv2.imwrite(clothe_path, cv2.cvtColor(cloth_image, cv2.COLOR_RGB2BGR))
288
+ # cv2.imwrite(single_path, cv2.cvtColor(gen_image, cv2.COLOR_RGB2BGR))
289
+ # top_image_path = os.path.join(save_dir, 'top_z_' + cloth_image_name)
290
+ # top_half_cropped = resize_and_crop(gen_image, 512, 600, True, False)
291
+ # cv2.imwrite(top_image_path, cv2.cvtColor(top_half_cropped, cv2.COLOR_RGB2BGR))
292
 
293
 
294
 
295
+ # # Update the cloth directory and mask path for the bottom half processing
296
  cloth_dir1 = '/work/pink_girl/cloth/trou'
297
+ # fixed_ref_mask_path = os.path.join(image_parse_v3_dir, 'trou1.png')
298
+ cloth_image_names = os.listdir(cloth_dir1)[:50]
299
 
300
  # Second loop for the bottom half
301
  for cloth_image_name in cloth_image_names:
adbase-step=44375.ckpt → pink_girl/image-mask/bottom_jean.png RENAMED
File without changes
pink_girl/image-mask/bra_model_768.png ADDED

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pink_girl/image/bottom_jean.jpg ADDED
pink_girl/image/bra_model_768.jpg ADDED
pink_girl/out_bot/bottom_z_40195438_0129_1.jpg ADDED
pink_girl/out_bot/bottom_z_40414461_0839_1.jpg ADDED
pink_girl/out_bot/bottom_z_40903231_0788_1.jpg ADDED
pink_girl/out_bot/bottom_z_40947839_0430_1.jpg ADDED
pink_girl/out_bot/bottom_z_40947839_0907_1.jpg ADDED
pink_girl/out_bot/bottom_z_40955124_0888_1.jpg ADDED
pink_girl/out_bot/bottom_z_40979991_0565_1.jpg ADDED
pink_girl/out_bot/bottom_z_41227558_0060_1.jpg ADDED
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pink_girl/out_bot/bottom_z_41612835_0416_1.jpg ADDED
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pink_girl/out_bot/bottom_z_42331568_0409_1.jpg ADDED