Spaces:
Runtime error
Runtime error
fix bugs
Browse files
app.py
CHANGED
@@ -28,8 +28,11 @@ def process_image(image, prompt):
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outputs = model(**inputs)
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preds = outputs.logits
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filename =
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-
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return Image.open("mask.png").convert("RGB")
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@@ -39,8 +42,8 @@ def read_content(file_path):
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return content
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def predict(
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width, height =
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if width < height:
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factor = width / 512.0
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width = 512
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@@ -51,10 +54,10 @@ def predict(dict, text_query, reference, scale, seed, step):
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height = 512
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width = int((width / factor) / 8.0) * 8
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init_image =
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mask =
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generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None
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output = pipe(
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image=init_image,
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@@ -122,7 +125,7 @@ with image_blocks as demo:
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with gr.Box():
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with gr.Row():
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with gr.Column():
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image = gr.Image(source="upload",
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text = gr.Textbox(lines=1, placeholder="Clothing item you want to replace...")
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reference = gr.Image(source="upload", elem_id="image_upload", type="pil", label="Reference Image")
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@@ -146,11 +149,25 @@ with image_blocks as demo:
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with gr.Row():
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with gr.Column():
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gr.Examples(
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with gr.Column():
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gr.Examples(
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btn.click(
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share_button.click(None, [], [], _js=share_js)
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gr.HTML(
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outputs = model(**inputs)
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preds = outputs.logits
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filename = "mask.png"
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preds = torch.sigmoid(preds)
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preds[preds >= 0.5] = 1
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preds[preds < 0.5] = 0
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plt.imsave(filename, preds)
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return Image.open("mask.png").convert("RGB")
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return content
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def predict(input_image, text_query, reference, scale, seed, step):
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width, height = input_image.size
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if width < height:
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factor = width / 512.0
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width = 512
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height = 512
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width = int((width / factor) / 8.0) * 8
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init_image = input_image.convert("RGB").resize((width, height))
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mask = process_image(input_image, text_query).resize((width, height))
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#mask = dict["mask"].convert("RGB").resize((width, height))
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generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None
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output = pipe(
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image=init_image,
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with gr.Box():
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with gr.Row():
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with gr.Column():
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image = gr.Image(source="upload", elem_id="image_upload", type="pil", label="Source Image")
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text = gr.Textbox(lines=1, placeholder="Clothing item you want to replace...")
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reference = gr.Image(source="upload", elem_id="image_upload", type="pil", label="Reference Image")
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with gr.Row():
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with gr.Column():
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gr.Examples(
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image_list,
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inputs=[image],
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label="Examples - Source Image",
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examples_per_page=12
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)
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with gr.Column():
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gr.Examples(
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ref_list,
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inputs=[reference],
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label="Examples - Reference Image",
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examples_per_page=12
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)
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btn.click(
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fn=predict,
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inputs=[image, text, reference, guidance, seed, steps],
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outputs=[image_out, community_icon, loading_icon, share_button]
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)
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share_button.click(None, [], [], _js=share_js)
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gr.HTML(
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