Tony Lian commited on
Commit
2335a8f
1 Parent(s): a55a1c5

Add autocast

Browse files
Files changed (46) hide show
  1. app.py +5 -4
  2. generation.py +46 -49
  3. gradio_cached_examples/39/Generated image/32ac0e0e-135a-404c-a1ee-53fdbc919db6/6e96ae22067936bf00a4f9f9415775f561fd0152/image.png +0 -0
  4. gradio_cached_examples/39/Generated image/32ac0e0e-135a-404c-a1ee-53fdbc919db6/captions.json +0 -1
  5. gradio_cached_examples/39/Generated image/5541f42f-a5c4-4c90-ae9c-389d0f0ea11a/captions.json +0 -1
  6. gradio_cached_examples/39/Generated image/5541f42f-a5c4-4c90-ae9c-389d0f0ea11a/e8933d4d2aff4203da4600fd6eb763a04c8667ff/image.png +0 -0
  7. gradio_cached_examples/39/Generated image/7dbf49b5-a987-4285-9ecb-899fc0897489/1ba27d75ea6c232428e503a0336d8eb3c346c0b3/image.png +0 -0
  8. gradio_cached_examples/39/Generated image/7dbf49b5-a987-4285-9ecb-899fc0897489/captions.json +0 -1
  9. gradio_cached_examples/39/Generated image/ae08bef2-f889-441a-ba1e-026445bb386a/1a312139177423e79631a7bf40aa1ac531efb744/image.png +0 -0
  10. gradio_cached_examples/39/Generated image/ae08bef2-f889-441a-ba1e-026445bb386a/captions.json +0 -1
  11. gradio_cached_examples/39/Generated image/d216beac-010e-4466-856c-9d92e471654c/90a51edff815fd0aaef1864d6784583e800be8d8/image.png +0 -0
  12. gradio_cached_examples/39/Generated image/d216beac-010e-4466-856c-9d92e471654c/captions.json +0 -1
  13. gradio_cached_examples/39/log.csv +0 -6
  14. gradio_cached_examples/40/Generated image/2b8c8fa6-273e-4993-b984-ca766b7fa093/6b8454f7801357c4c41076b4281ff36cc3c168d1/image.png +0 -0
  15. gradio_cached_examples/40/Generated image/2b8c8fa6-273e-4993-b984-ca766b7fa093/captions.json +1 -0
  16. gradio_cached_examples/40/Generated image/5cc41c19-e968-478e-b144-5b8ba3d07be1/65c5ef22af85300a0da31b44b1ad679a47eecc25/image.png +0 -0
  17. gradio_cached_examples/40/Generated image/5cc41c19-e968-478e-b144-5b8ba3d07be1/captions.json +1 -0
  18. gradio_cached_examples/40/Generated image/cd999256-9a24-4a5b-a897-5c5fa56c5a67/101f36d55ac3f9ebcf7ff5647da0d7acb4994c97/image.png +0 -0
  19. gradio_cached_examples/40/Generated image/cd999256-9a24-4a5b-a897-5c5fa56c5a67/captions.json +1 -0
  20. gradio_cached_examples/40/Generated image/e5bbe48b-6f7d-45c9-b75f-38f1709e0026/210e77149171a376e7be7a733564930e356849db/image.png +0 -0
  21. gradio_cached_examples/40/Generated image/e5bbe48b-6f7d-45c9-b75f-38f1709e0026/captions.json +1 -0
  22. gradio_cached_examples/40/Generated image/eb50d204-9a80-4e66-82a4-b24be17a05c2/44f995a0ec0c935f5881edd8af7f10e857e1a968/image.png +0 -0
  23. gradio_cached_examples/40/Generated image/eb50d204-9a80-4e66-82a4-b24be17a05c2/captions.json +1 -0
  24. gradio_cached_examples/40/log.csv +6 -0
  25. gradio_cached_examples/49/Generated image/569b2539-1b09-422e-8f04-28e85cb5ce6b/79b47dee4bf06f02baaddf31631dadf4f0a77b1b/image.png +0 -0
  26. gradio_cached_examples/49/Generated image/569b2539-1b09-422e-8f04-28e85cb5ce6b/captions.json +0 -1
  27. gradio_cached_examples/49/Generated image/7ca4de19-dacd-433a-9bda-44a30411773a/captions.json +0 -1
  28. gradio_cached_examples/49/Generated image/7ca4de19-dacd-433a-9bda-44a30411773a/da41c41cef06d8895f87bd51bccacb9e5ee6fc13/image.png +0 -0
  29. gradio_cached_examples/49/Generated image/9d74cf63-2741-4aa1-9b9d-284ce36b1272/916b46e1b9e7e59a0f42ea2e0e9d3ac2077ddb29/image.png +0 -0
  30. gradio_cached_examples/49/Generated image/9d74cf63-2741-4aa1-9b9d-284ce36b1272/captions.json +0 -1
  31. gradio_cached_examples/49/Generated image/d1cff19c-eda7-411a-97bd-598780ee1514/111213a2bec11fbeb98d5cf421ff3f1e90ac2a6f/image.png +0 -0
  32. gradio_cached_examples/49/Generated image/d1cff19c-eda7-411a-97bd-598780ee1514/captions.json +0 -1
  33. gradio_cached_examples/49/Generated image/ff249b87-f078-4ed7-b702-d9c026c2ae0b/30ac54337ceb5917e94befaaa6939bdb2970ea50/image.png +0 -0
  34. gradio_cached_examples/49/Generated image/ff249b87-f078-4ed7-b702-d9c026c2ae0b/captions.json +0 -1
  35. gradio_cached_examples/49/log.csv +0 -6
  36. gradio_cached_examples/50/Generated image/2b20f451-c8d6-4f26-b580-85a54989b5e7/captions.json +1 -0
  37. gradio_cached_examples/50/Generated image/2b20f451-c8d6-4f26-b580-85a54989b5e7/e73c626c4dd21a7ad80767910261adf9442952fc/image.png +0 -0
  38. gradio_cached_examples/50/Generated image/3ef81752-e136-466d-b5d0-fa2ddec37971/6863bcdf1ddd78ec6b38cb7f7e54dfd02042cfc8/image.png +0 -0
  39. gradio_cached_examples/50/Generated image/3ef81752-e136-466d-b5d0-fa2ddec37971/captions.json +1 -0
  40. gradio_cached_examples/50/Generated image/460ea7e5-92af-4b13-9c5d-1386164789d7/c881ad29f622a8f1d9a88854d93ec05142de78c0/image.png +0 -0
  41. gradio_cached_examples/50/Generated image/460ea7e5-92af-4b13-9c5d-1386164789d7/captions.json +1 -0
  42. gradio_cached_examples/50/Generated image/8c451715-7470-46fc-9634-e16f88e98e49/5107323699a702f3dbb8cac7480802bd1ce00aa8/image.png +0 -0
  43. gradio_cached_examples/50/Generated image/8c451715-7470-46fc-9634-e16f88e98e49/captions.json +1 -0
  44. gradio_cached_examples/50/Generated image/bbaa5527-7cf2-47e4-aa03-6d68ecbaa65b/62563c47f44f246d810891c182da583bab12f8a0/image.png +0 -0
  45. gradio_cached_examples/50/Generated image/bbaa5527-7cf2-47e4-aa03-6d68ecbaa65b/captions.json +1 -0
  46. gradio_cached_examples/50/log.csv +6 -0
app.py CHANGED
@@ -88,7 +88,7 @@ def get_layout_image(response):
88
  def get_layout_image_gallery(response):
89
  return [get_layout_image(response)]
90
 
91
- def get_ours_image(response, seed, num_inference_steps=20, dpm_scheduler=True, overall_prompt_override="", fg_seed_start=20, fg_blending_ratio=0.1, frozen_step_ratio=0.4, gligen_scheduled_sampling_beta=0.3, so_negative_prompt=DEFAULT_SO_NEGATIVE_PROMPT, overall_negative_prompt=DEFAULT_OVERALL_NEGATIVE_PROMPT, show_so_imgs=False, scale_boxes=False):
92
  if response == "":
93
  response = layout_placeholder
94
  gen_boxes, bg_prompt = parse_input(response)
@@ -107,7 +107,7 @@ def get_ours_image(response, seed, num_inference_steps=20, dpm_scheduler=True, o
107
 
108
  image_np, so_img_list = run_ours(
109
  spec, bg_seed=seed, overall_prompt_override=overall_prompt_override, fg_seed_start=fg_seed_start,
110
- fg_blending_ratio=fg_blending_ratio,frozen_step_ratio=frozen_step_ratio,
111
  gligen_scheduled_sampling_beta=gligen_scheduled_sampling_beta, num_inference_steps=num_inference_steps, scheduler_key=scheduler_key,
112
  so_negative_prompt=so_negative_prompt, overall_negative_prompt=overall_negative_prompt
113
  )
@@ -242,7 +242,8 @@ with gr.Blocks(
242
  frozen_step_ratio = gr.Slider(0, 1, value=0.4, step=0.1, label="Foreground frozen steps ratio (higher: preserve object attributes; lower: higher coherence; set to 0: (almost) equivalent to vanilla GLIGEN except details)")
243
  gligen_scheduled_sampling_beta = gr.Slider(0, 1, value=0.3, step=0.1, label="GLIGEN guidance steps ratio (the beta value)")
244
  num_inference_steps = gr.Slider(1, 50, value=20, step=1, label="Number of inference steps")
245
- dpm_scheduler = gr.Checkbox(label="Use DPM scheduler (unchecked: DDIM scheduler, may have better coherence, recommend 50 inference steps)", show_label=False, value=True)
 
246
  fg_seed_start = gr.Slider(0, 10000, value=20, step=1, label="Seed for foreground variation")
247
  fg_blending_ratio = gr.Slider(0, 1, value=0.1, step=0.01, label="Variations added to foreground for single object generation (0: no variation, 1: max variation)")
248
  so_negative_prompt = gr.Textbox(lines=1, label="Negative prompt for single object generation", value=DEFAULT_SO_NEGATIVE_PROMPT)
@@ -256,7 +257,7 @@ with gr.Blocks(
256
  label="Generated image", show_label=False, elem_id="gallery", columns=[1], rows=[1], object_fit="contain", preview=True
257
  )
258
  visualize_btn.click(fn=get_layout_image_gallery, inputs=response, outputs=gallery, api_name="visualize-layout")
259
- generate_btn.click(fn=get_ours_image, inputs=[response, seed, num_inference_steps, dpm_scheduler, overall_prompt_override, fg_seed_start, fg_blending_ratio, frozen_step_ratio, gligen_scheduled_sampling_beta, so_negative_prompt, overall_negative_prompt, show_so_imgs, scale_boxes], outputs=gallery, api_name="layout-to-image")
260
 
261
  gr.Examples(
262
  examples=stage2_examples,
 
88
  def get_layout_image_gallery(response):
89
  return [get_layout_image(response)]
90
 
91
+ def get_ours_image(response, seed, num_inference_steps=20, dpm_scheduler=True, use_autocast=False, overall_prompt_override="", fg_seed_start=20, fg_blending_ratio=0.1, frozen_step_ratio=0.4, gligen_scheduled_sampling_beta=0.3, so_negative_prompt=DEFAULT_SO_NEGATIVE_PROMPT, overall_negative_prompt=DEFAULT_OVERALL_NEGATIVE_PROMPT, show_so_imgs=False, scale_boxes=False):
92
  if response == "":
93
  response = layout_placeholder
94
  gen_boxes, bg_prompt = parse_input(response)
 
107
 
108
  image_np, so_img_list = run_ours(
109
  spec, bg_seed=seed, overall_prompt_override=overall_prompt_override, fg_seed_start=fg_seed_start,
110
+ fg_blending_ratio=fg_blending_ratio,frozen_step_ratio=frozen_step_ratio, use_autocast=use_autocast,
111
  gligen_scheduled_sampling_beta=gligen_scheduled_sampling_beta, num_inference_steps=num_inference_steps, scheduler_key=scheduler_key,
112
  so_negative_prompt=so_negative_prompt, overall_negative_prompt=overall_negative_prompt
113
  )
 
242
  frozen_step_ratio = gr.Slider(0, 1, value=0.4, step=0.1, label="Foreground frozen steps ratio (higher: preserve object attributes; lower: higher coherence; set to 0: (almost) equivalent to vanilla GLIGEN except details)")
243
  gligen_scheduled_sampling_beta = gr.Slider(0, 1, value=0.3, step=0.1, label="GLIGEN guidance steps ratio (the beta value)")
244
  num_inference_steps = gr.Slider(1, 50, value=20, step=1, label="Number of inference steps")
245
+ dpm_scheduler = gr.Checkbox(label="Use DPM scheduler (unchecked: DDIM scheduler, may have better coherence, recommend 50 or even more inference steps)", show_label=False, value=True)
246
+ use_autocast = gr.Checkbox(label="Use FP16 Mixed Precision", show_label=False, value=True)
247
  fg_seed_start = gr.Slider(0, 10000, value=20, step=1, label="Seed for foreground variation")
248
  fg_blending_ratio = gr.Slider(0, 1, value=0.1, step=0.01, label="Variations added to foreground for single object generation (0: no variation, 1: max variation)")
249
  so_negative_prompt = gr.Textbox(lines=1, label="Negative prompt for single object generation", value=DEFAULT_SO_NEGATIVE_PROMPT)
 
257
  label="Generated image", show_label=False, elem_id="gallery", columns=[1], rows=[1], object_fit="contain", preview=True
258
  )
259
  visualize_btn.click(fn=get_layout_image_gallery, inputs=response, outputs=gallery, api_name="visualize-layout")
260
+ generate_btn.click(fn=get_ours_image, inputs=[response, seed, num_inference_steps, dpm_scheduler, use_autocast, overall_prompt_override, fg_seed_start, fg_blending_ratio, frozen_step_ratio, gligen_scheduled_sampling_beta, so_negative_prompt, overall_negative_prompt, show_so_imgs, scale_boxes], outputs=gallery, api_name="layout-to-image")
261
 
262
  gr.Examples(
263
  examples=stage2_examples,
generation.py CHANGED
@@ -76,8 +76,8 @@ def get_masked_latents_all_list(so_prompt_phrase_word_box_list, input_latents_li
76
 
77
  def run(
78
  spec, bg_seed = 1, overall_prompt_override="", fg_seed_start = 20, frozen_step_ratio=0.4, gligen_scheduled_sampling_beta = 0.3, num_inference_steps = 20,
79
- so_center_box = False, fg_blending_ratio = 0.1, scheduler_key='dpm_scheduler', so_negative_prompt = DEFAULT_SO_NEGATIVE_PROMPT, overall_negative_prompt = DEFAULT_OVERALL_NEGATIVE_PROMPT, so_horizontal_center_only = True,
80
- align_with_overall_bboxes = False, horizontal_shift_only = True
81
  ):
82
  """
83
  so_center_box: using centered box in single object generation
@@ -111,62 +111,59 @@ def run(
111
  discourage_mask_below_confidence=discourage_mask_below_confidence, discourage_mask_below_coarse_iou=discourage_mask_below_coarse_iou,
112
  height=height, width=width, H=H, W=W
113
  )
114
-
115
 
116
  # Note that so and overall use different negative prompts
117
 
118
- so_prompts = [item[0] for item in so_prompt_phrase_word_box_list]
119
- if so_prompts:
120
- so_input_embeddings = models.encode_prompts(prompts=so_prompts, tokenizer=tokenizer, text_encoder=text_encoder, negative_prompt=so_negative_prompt, one_uncond_input_only=True)
121
- else:
122
- so_input_embeddings = []
123
-
124
- overall_input_embeddings = models.encode_prompts(prompts=[overall_prompt], tokenizer=tokenizer, negative_prompt=overall_negative_prompt, text_encoder=text_encoder)
125
-
126
 
 
 
 
 
 
 
 
 
 
 
 
127
 
128
-
129
- input_latents_list, latents_bg = latents.get_input_latents_list(
130
- model_dict, bg_seed=bg_seed, fg_seed_start=fg_seed_start,
131
- so_boxes=so_boxes, fg_blending_ratio=fg_blending_ratio, height=height, width=width, verbose=False
132
- )
133
- latents_all_list, mask_tensor_list, so_img_list = get_masked_latents_all_list(
134
- so_prompt_phrase_word_box_list, input_latents_list,
135
- gligen_scheduled_sampling_beta=gligen_scheduled_sampling_beta,
136
- sam_refine_kwargs=sam_refine_kwargs, so_input_embeddings=so_input_embeddings, num_inference_steps=num_inference_steps, scheduler_key=scheduler_key, verbose=verbose
137
- )
138
-
139
-
140
 
141
- composed_latents, foreground_indices, offset_list = latents.compose_latents_with_alignment(
142
- model_dict, latents_all_list, mask_tensor_list, num_inference_steps,
143
- overall_batch_size, height, width, latents_bg=latents_bg,
144
- align_with_overall_bboxes=align_with_overall_bboxes, overall_bboxes=overall_bboxes,
145
- horizontal_shift_only=horizontal_shift_only
146
- )
147
-
148
- overall_bboxes_flattened, overall_phrases_flattened = [], []
149
- for overall_bboxes_item, overall_phrase in zip(overall_bboxes, overall_phrases):
150
- for overall_bbox in overall_bboxes_item:
151
- overall_bboxes_flattened.append(overall_bbox)
152
- overall_phrases_flattened.append(overall_phrase)
153
 
154
- # Generate with composed latents
155
 
156
- # Foreground should be frozen
157
- frozen_mask = foreground_indices != 0
158
-
159
- regen_latents, images = pipelines.generate_gligen(
160
- model_dict, composed_latents, overall_input_embeddings, num_inference_steps,
161
- overall_bboxes_flattened, overall_phrases_flattened, guidance_scale=guidance_scale,
162
- gligen_scheduled_sampling_beta=gligen_scheduled_sampling_beta,
163
- frozen_steps=frozen_steps, frozen_mask=frozen_mask, scheduler_key=scheduler_key
164
- )
165
 
166
- print(f"Generation with spatial guidance from input latents and first {frozen_steps} steps frozen (directly from the composed latents input)")
167
- print("Generation from composed latents (with semantic guidance)")
168
 
169
- # display(Image.fromarray(images[0]), "img", run_ind)
170
-
171
  return images[0], so_img_list
172
 
 
76
 
77
  def run(
78
  spec, bg_seed = 1, overall_prompt_override="", fg_seed_start = 20, frozen_step_ratio=0.4, gligen_scheduled_sampling_beta = 0.3, num_inference_steps = 20,
79
+ so_center_box = False, fg_blending_ratio = 0.1, scheduler_key='dpm_scheduler', so_negative_prompt = DEFAULT_SO_NEGATIVE_PROMPT, overall_negative_prompt = DEFAULT_OVERALL_NEGATIVE_PROMPT, so_horizontal_center_only = True,
80
+ align_with_overall_bboxes = False, horizontal_shift_only = True, use_autocast = False
81
  ):
82
  """
83
  so_center_box: using centered box in single object generation
 
111
  discourage_mask_below_confidence=discourage_mask_below_confidence, discourage_mask_below_coarse_iou=discourage_mask_below_coarse_iou,
112
  height=height, width=width, H=H, W=W
113
  )
 
114
 
115
  # Note that so and overall use different negative prompts
116
 
117
+ with torch.autocast("cuda", enabled=use_autocast):
118
+ so_prompts = [item[0] for item in so_prompt_phrase_word_box_list]
119
+ if so_prompts:
120
+ so_input_embeddings = models.encode_prompts(prompts=so_prompts, tokenizer=tokenizer, text_encoder=text_encoder, negative_prompt=so_negative_prompt, one_uncond_input_only=True)
121
+ else:
122
+ so_input_embeddings = []
 
 
123
 
124
+ overall_input_embeddings = models.encode_prompts(prompts=[overall_prompt], tokenizer=tokenizer, negative_prompt=overall_negative_prompt, text_encoder=text_encoder)
125
+
126
+ input_latents_list, latents_bg = latents.get_input_latents_list(
127
+ model_dict, bg_seed=bg_seed, fg_seed_start=fg_seed_start,
128
+ so_boxes=so_boxes, fg_blending_ratio=fg_blending_ratio, height=height, width=width, verbose=False
129
+ )
130
+ latents_all_list, mask_tensor_list, so_img_list = get_masked_latents_all_list(
131
+ so_prompt_phrase_word_box_list, input_latents_list,
132
+ gligen_scheduled_sampling_beta=gligen_scheduled_sampling_beta,
133
+ sam_refine_kwargs=sam_refine_kwargs, so_input_embeddings=so_input_embeddings, num_inference_steps=num_inference_steps, scheduler_key=scheduler_key, verbose=verbose
134
+ )
135
 
136
+
 
 
 
 
 
 
 
 
 
 
 
137
 
138
+ composed_latents, foreground_indices, offset_list = latents.compose_latents_with_alignment(
139
+ model_dict, latents_all_list, mask_tensor_list, num_inference_steps,
140
+ overall_batch_size, height, width, latents_bg=latents_bg,
141
+ align_with_overall_bboxes=align_with_overall_bboxes, overall_bboxes=overall_bboxes,
142
+ horizontal_shift_only=horizontal_shift_only
143
+ )
144
+
145
+ overall_bboxes_flattened, overall_phrases_flattened = [], []
146
+ for overall_bboxes_item, overall_phrase in zip(overall_bboxes, overall_phrases):
147
+ for overall_bbox in overall_bboxes_item:
148
+ overall_bboxes_flattened.append(overall_bbox)
149
+ overall_phrases_flattened.append(overall_phrase)
150
 
151
+ # Generate with composed latents
152
 
153
+ # Foreground should be frozen
154
+ frozen_mask = foreground_indices != 0
155
+
156
+ regen_latents, images = pipelines.generate_gligen(
157
+ model_dict, composed_latents, overall_input_embeddings, num_inference_steps,
158
+ overall_bboxes_flattened, overall_phrases_flattened, guidance_scale=guidance_scale,
159
+ gligen_scheduled_sampling_beta=gligen_scheduled_sampling_beta,
160
+ frozen_steps=frozen_steps, frozen_mask=frozen_mask, scheduler_key=scheduler_key
161
+ )
162
 
163
+ print(f"Generation with spatial guidance from input latents and first {frozen_steps} steps frozen (directly from the composed latents input)")
164
+ print("Generation from composed latents (with semantic guidance)")
165
 
166
+ # display(Image.fromarray(images[0]), "img", run_ind)
167
+
168
  return images[0], so_img_list
169
 
gradio_cached_examples/39/Generated image/32ac0e0e-135a-404c-a1ee-53fdbc919db6/6e96ae22067936bf00a4f9f9415775f561fd0152/image.png DELETED
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gradio_cached_examples/39/Generated image/5541f42f-a5c4-4c90-ae9c-389d0f0ea11a/captions.json DELETED
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gradio_cached_examples/39/Generated image/5541f42f-a5c4-4c90-ae9c-389d0f0ea11a/e8933d4d2aff4203da4600fd6eb763a04c8667ff/image.png DELETED
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