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Update app.py
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app.py
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@@ -2,16 +2,25 @@ import gradio as gr
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from PIL import Image
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import os
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import time
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from src.utils import change_background, matte
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def process_images(uploaded_files, background_color):
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# Add debugging statement
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print(f"background_color received: {background_color}")
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# Default value check
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if background_color is None:
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-
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hexmap = {
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"Transparent (PNG)": "#000000",
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@@ -38,6 +47,33 @@ def process_images(uploaded_files, background_color):
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return results, "\n".join(times)
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with gr.Blocks() as demo:
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gr.Markdown("""
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# AI Photo Background Removal
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@@ -48,7 +84,7 @@ with gr.Blocks() as demo:
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with gr.Row():
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folder_input = gr.Files(type="filepath", label="Upload your photos here")
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bg_color = gr.Dropdown(choices=["Transparent (PNG)", "White", "Black", "Green", "Red", "Blue"], label="Choose background color")
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output_images = gr.Gallery(label="Processed Images")
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processing_times = gr.Textbox(label="Processing Times")
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@@ -63,4 +99,4 @@ with gr.Blocks() as demo:
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)
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if __name__ == "__main__":
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demo.launch(
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from PIL import Image
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import os
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import time
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import json
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from fastapi import FastAPI
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from pydantic import BaseModel
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from src.utils import change_background, matte
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app = FastAPI()
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class ImageRequest(BaseModel):
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image: str # Base64 encoded image
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background_color: str
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def process_images(uploaded_files, background_color):
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# Add debugging statement
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print(f"background_color received: {background_color}")
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# Default value check
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if background_color is None:
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background_color = "Transparent (PNG)"
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hexmap = {
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"Transparent (PNG)": "#000000",
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return results, "\n".join(times)
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@app.post("/process")
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def api_process_images(request: ImageRequest):
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image_data = request.image
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background_color = request.background_color
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# Convert base64 to PIL image
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img_input = Image.open(BytesIO(base64.b64decode(image_data)))
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hexmap = {
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"Transparent (PNG)": "#000000",
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"Black": "#000000",
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"White": "#FFFFFF",
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"Green": "#22EE22",
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"Red": "#EE2222",
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"Blue": "#2222EE",
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}
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alpha = 0.0 if background_color == "Transparent (PNG)" else 1.0
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img_matte = matte(img_input)
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img_output = change_background(img_input, img_matte, background_alpha=alpha, background_hex=hexmap[background_color])
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buffered = BytesIO()
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img_output.save(buffered, format="PNG")
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img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
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return {"image": img_str}
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with gr.Blocks() as demo:
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gr.Markdown("""
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# AI Photo Background Removal
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with gr.Row():
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folder_input = gr.Files(type="filepath", label="Upload your photos here")
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bg_color = gr.Dropdown(choices=["Transparent (PNG)", "White", "Black", "Green", "Red", "Blue"], label="Choose background color", value="Transparent (PNG)")
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output_images = gr.Gallery(label="Processed Images")
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processing_times = gr.Textbox(label="Processing Times")
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)
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if __name__ == "__main__":
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demo.launch()
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