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yisol commited on
Commit
ab2e314
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1 Parent(s): c123434

add auto crop

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Files changed (1) hide show
  1. app.py +31 -6
app.py CHANGED
@@ -122,7 +122,7 @@ pipe = TryonPipeline.from_pretrained(
122
  pipe.unet_encoder = UNet_Encoder
123
 
124
  @spaces.GPU
125
- def start_tryon(dict,garm_img,garment_des,is_checked,denoise_steps,seed):
126
  device = "cuda"
127
 
128
  openpose_model.preprocessor.body_estimation.model.to(device)
@@ -130,8 +130,23 @@ def start_tryon(dict,garm_img,garment_des,is_checked,denoise_steps,seed):
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  pipe.unet_encoder.to(device)
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132
  garm_img= garm_img.convert("RGB").resize((768,1024))
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- human_img = dict["background"].resize((768,1024)).convert("RGB")
134
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
135
  if is_checked:
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  keypoints = openpose_model(human_img.resize((384,512)))
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  model_parse, _ = parsing_model(human_img.resize((384,512)))
@@ -217,7 +232,14 @@ def start_tryon(dict,garm_img,garment_des,is_checked,denoise_steps,seed):
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  ip_adapter_image = garm_img.resize((768,1024)),
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  guidance_scale=2.0,
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  )[0]
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- return images[0], mask_gray
 
 
 
 
 
 
 
221
 
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  garm_list = os.listdir(os.path.join(example_path,"cloth"))
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  garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list]
@@ -241,7 +263,10 @@ with image_blocks as demo:
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  with gr.Column():
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  imgs = gr.ImageEditor(sources='upload', type="pil", label='Human. Mask with pen or use auto-masking', interactive=True)
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  with gr.Row():
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- is_checked = gr.Checkbox(label="Yes", info="Use auto-generated mask (Takes 5 more seconds)",value=True)
 
 
 
245
  example = gr.Examples(
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  inputs=imgs,
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  examples_per_page=10,
@@ -255,7 +280,7 @@ with image_blocks as demo:
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  prompt = gr.Textbox(placeholder="Description of garment ex) Short Sleeve Round Neck T-shirts", show_label=False, elem_id="prompt")
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  example = gr.Examples(
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  inputs=garm_img,
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- examples_per_page=10,
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  examples=garm_list_path)
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  with gr.Column():
261
  # image_out = gr.Image(label="Output", elem_id="output-img", height=400)
@@ -275,7 +300,7 @@ with image_blocks as demo:
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  seed = gr.Number(label="Seed", minimum=-1, maximum=2147483647, step=1, value=42)
276
 
277
 
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- try_button.click(fn=start_tryon, inputs=[imgs, garm_img, prompt, is_checked, denoise_steps, seed], outputs=[image_out,masked_img], api_name='tryon')
279
 
280
 
281
 
 
122
  pipe.unet_encoder = UNet_Encoder
123
 
124
  @spaces.GPU
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+ def start_tryon(dict,garm_img,garment_des,is_checked,is_checked_crop,denoise_steps,seed):
126
  device = "cuda"
127
 
128
  openpose_model.preprocessor.body_estimation.model.to(device)
 
130
  pipe.unet_encoder.to(device)
131
 
132
  garm_img= garm_img.convert("RGB").resize((768,1024))
133
+ human_img_orig = dict["background"].resize((768,1024)).convert("RGB")
134
 
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+ if is_checked_crop:
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+ width, height = human_img_orig.size
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+ target_width = int(min(width, height * (3 / 4)))
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+ target_height = int(min(height, width * (4 / 3)))
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+ left = (width - target_width) / 2
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+ top = (height - target_height) / 2
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+ right = (width + target_width) / 2
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+ bottom = (height + target_height) / 2
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+ cropped_img = human_img_orig.crop((left, top, right, bottom))
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+ crop_size = cropped_img.size
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+ human_img = cropped_img.resize((768,1024))
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+ else:
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+ human_img = human_img_orig.resize((768,1024))
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+
149
+
150
  if is_checked:
151
  keypoints = openpose_model(human_img.resize((384,512)))
152
  model_parse, _ = parsing_model(human_img.resize((384,512)))
 
232
  ip_adapter_image = garm_img.resize((768,1024)),
233
  guidance_scale=2.0,
234
  )[0]
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+
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+ if is_checked_crop:
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+ out_img = images[0].resize(crop_size)
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+ human_img_orig.paste(out_img, (int(left), int(top)))
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+ return human_img_orig, mask_gray
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+ else:
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+ return images[0], mask_gray
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+ # return images[0], mask_gray
243
 
244
  garm_list = os.listdir(os.path.join(example_path,"cloth"))
245
  garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list]
 
263
  with gr.Column():
264
  imgs = gr.ImageEditor(sources='upload', type="pil", label='Human. Mask with pen or use auto-masking', interactive=True)
265
  with gr.Row():
266
+ is_checked = gr.Checkbox(label="Yes", info="Use auto-generated mask (Takes 5 seconds)",value=True)
267
+ with gr.Row():
268
+ is_checked_crop = gr.Checkbox(label="Yes", info="Use auto-crop & resizing",value=False)
269
+
270
  example = gr.Examples(
271
  inputs=imgs,
272
  examples_per_page=10,
 
280
  prompt = gr.Textbox(placeholder="Description of garment ex) Short Sleeve Round Neck T-shirts", show_label=False, elem_id="prompt")
281
  example = gr.Examples(
282
  inputs=garm_img,
283
+ examples_per_page=8,
284
  examples=garm_list_path)
285
  with gr.Column():
286
  # image_out = gr.Image(label="Output", elem_id="output-img", height=400)
 
300
  seed = gr.Number(label="Seed", minimum=-1, maximum=2147483647, step=1, value=42)
301
 
302
 
303
+ try_button.click(fn=start_tryon, inputs=[imgs, garm_img, prompt, is_checked,is_checked_crop, denoise_steps, seed], outputs=[image_out,masked_img], api_name='tryon')
304
 
305
 
306