Spaces:
Running
on
Zero
Running
on
Zero
v3p6
Browse files
app.py
CHANGED
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@@ -66,11 +66,25 @@ def load_pipeline(model_name):
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def parse_json_parameters(json_str):
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try:
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params = json.loads(json_str)
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required_keys = ['prompt', 'negative_prompt', '
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for key in required_keys:
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if key not in params:
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raise ValueError(f"Missing required key: {key}")
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except json.JSONDecodeError:
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raise ValueError("Invalid JSON format")
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except Exception as e:
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@@ -104,6 +118,7 @@ def generate(
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guidance_scale = params['guidance_scale']
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num_inference_steps = params['num_inference_steps']
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sampler = params['sampler']
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except ValueError as e:
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raise gr.Error(str(e))
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@@ -200,24 +215,14 @@ generation_history = []
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# Function to update the history list
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def update_history_list():
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<img src='data:image/png;base64,{utils.image_to_base64(item["image"])}'
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style='width: 100px; height: 100px; object-fit: cover;'
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onclick='handle_image_click({idx})' />
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<p style='width: 100px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis;'>
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{item["prompt"]}
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</p>
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</div>
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"""
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html += "</div>"
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return html
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# Function to handle image click in history
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def handle_image_click(
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selected = generation_history[
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return selected["image"], json.dumps(selected["metadata"], indent=2)
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# Modify the generate function to add results to the history
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@@ -232,7 +237,7 @@ def generate_and_update_history(*args, **kwargs):
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})
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if len(generation_history) > 10: # Limit history to 10 items
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generation_history.pop()
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return images, metadata, gr.update(
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if torch.cuda.is_available():
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pipe = load_pipeline(MODEL)
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@@ -268,10 +273,8 @@ with gr.Blocks(css="style.css") as demo:
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variant="primary",
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scale=0
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)
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result = gr.
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label="Result",
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columns=1,
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preview=True,
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show_label=False
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)
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with gr.Accordion(label="Advanced Settings", open=False):
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@@ -354,8 +357,8 @@ with gr.Blocks(css="style.css") as demo:
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generate_from_json = gr.Button("Generate from JSON")
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# Add history accordion
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with gr.Accordion("Generation History",
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with gr.Row():
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selected_image = gr.Image(label="Selected Image", interactive=False)
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selected_metadata = gr.JSON(label="Selected Metadata", show_label=False)
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@@ -408,10 +411,7 @@ with gr.Blocks(css="style.css") as demo:
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).then(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata,
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).then(
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fn=update_history_list,
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outputs=history_list
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)
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negative_prompt.submit(
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@@ -423,10 +423,7 @@ with gr.Blocks(css="style.css") as demo:
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).then(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata,
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).then(
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fn=update_history_list,
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outputs=history_list
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)
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run_button.click(
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@@ -438,23 +435,20 @@ with gr.Blocks(css="style.css") as demo:
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).then(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata,
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).then(
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fn=update_history_list,
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outputs=history_list
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)
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# Add event handler for generate_from_json button
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generate_from_json.click(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata,
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).then(
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fn=update_history_list,
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outputs=history_list
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)
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# Add
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demo.queue(max_size=20).launch(debug=IS_COLAB, share=IS_COLAB)
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def parse_json_parameters(json_str):
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try:
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params = json.loads(json_str)
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required_keys = ['prompt', 'negative_prompt', 'resolution', 'guidance_scale', 'num_inference_steps', 'seed', 'sampler']
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for key in required_keys:
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if key not in params:
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raise ValueError(f"Missing required key: {key}")
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# Parse resolution
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width, height = map(int, params['resolution'].split(' x '))
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return {
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'prompt': params['prompt'],
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'negative_prompt': params['negative_prompt'],
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'seed': params['seed'],
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'width': width,
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'height': height,
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'guidance_scale': params['guidance_scale'],
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'num_inference_steps': params['num_inference_steps'],
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'sampler': params['sampler'],
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'use_upscaler': params.get('use_upscaler', False)
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}
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except json.JSONDecodeError:
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raise ValueError("Invalid JSON format")
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except Exception as e:
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guidance_scale = params['guidance_scale']
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num_inference_steps = params['num_inference_steps']
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sampler = params['sampler']
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use_upscaler = params['use_upscaler']
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except ValueError as e:
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raise gr.Error(str(e))
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# Function to update the history list
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def update_history_list():
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return [
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gr.Image.update(value=item["image"], visible=True)
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for item in generation_history
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]
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# Function to handle image click in history
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def handle_image_click(evt: gr.SelectData):
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selected = generation_history[evt.index]
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return selected["image"], json.dumps(selected["metadata"], indent=2)
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# Modify the generate function to add results to the history
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})
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if len(generation_history) > 10: # Limit history to 10 items
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generation_history.pop()
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return images[0], json.dumps(metadata, indent=2), gr.Gallery.update(value=update_history_list())
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if torch.cuda.is_available():
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pipe = load_pipeline(MODEL)
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variant="primary",
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scale=0
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)
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result = gr.Image(
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label="Result",
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show_label=False
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)
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with gr.Accordion(label="Advanced Settings", open=False):
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generate_from_json = gr.Button("Generate from JSON")
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# Add history accordion
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with gr.Accordion("Generation History", open=False) as history_accordion:
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history_gallery = gr.Gallery(label="History", show_label=False, elem_id="history_gallery").style(grid=5)
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with gr.Row():
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selected_image = gr.Image(label="Selected Image", interactive=False)
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selected_metadata = gr.JSON(label="Selected Metadata", show_label=False)
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).then(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata, history_gallery],
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)
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negative_prompt.submit(
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).then(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata, history_gallery],
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)
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run_button.click(
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).then(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata, history_gallery],
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)
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# Add event handler for generate_from_json button
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generate_from_json.click(
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fn=generate_and_update_history,
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inputs=inputs,
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outputs=[result, gr_metadata, history_gallery],
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)
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# Add event handler for image selection in history
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history_gallery.select(
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fn=handle_image_click,
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outputs=[selected_image, selected_metadata],
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)
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demo.queue(max_size=20).launch(debug=IS_COLAB, share=IS_COLAB)
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