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Update app.py
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app.py
CHANGED
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@@ -10,7 +10,6 @@ import tempfile
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import os
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import time
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import uuid
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import shutil
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# Load the pre-trained model
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print("Loading model...")
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@@ -34,7 +33,7 @@ def resize_image(image):
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# Background removal process
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def process(image, progress=gr.Progress()):
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if image is None:
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return None, None
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progress(0, desc="Starting processing...")
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@@ -85,23 +84,8 @@ def process(image, progress=gr.Progress()):
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output_array = np.array(new_im.convert("RGBA"))
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progress(1.0, desc="Done!")
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# Return the
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return output_array, filepath
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# Function to handle the download
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def download_image(filepath):
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if filepath and os.path.exists(filepath):
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filename = os.path.basename(filepath)
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# Create a new file in a web-accessible directory
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download_path = os.path.join("downloads", filename)
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os.makedirs("downloads", exist_ok=True)
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# Copy the file to the download directory
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shutil.copy2(filepath, download_path)
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# Return the file path for download
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return download_path
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return None
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# Gradio interface setup
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title = "Background Removal"
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@@ -109,86 +93,76 @@ description = r"""Background removal model developed by <a href='https://BRIA.AI
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examples = [['./input.jpg']]
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# Create
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background-color: #4CAF50 !important;
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color: white !important;
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border: none !important;
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padding: 10px
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text-align: center !important;
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text-decoration: none !important;
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display: inline-block !important;
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font-size: 16px !important;
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margin: 10px 0 !important;
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cursor: pointer !important;
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border-radius: 4px !important;
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}
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.
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background-color: #45a049 !important;
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}
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"""
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gr.Markdown(description)
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# Store the filepath
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filepath = gr.State()
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with gr.Row():
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with gr.Column(scale=1):
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input_image = gr.Image(type="numpy", label="Upload Image")
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with gr.Column(scale=1):
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output_image = gr.Image(type="numpy", label="Result")
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# Hidden file component for actual download
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download_file = gr.File(visible=False)
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# Custom styled download button
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with gr.Row():
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download_btn = gr.Button(
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"Download Image",
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visible=False,
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elem_classes=["download-button"]
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)
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# Set up example images
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gr.Examples(examples, inputs=input_image)
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# Process automatically when image is uploaded
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input_image.change(
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fn=process,
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inputs=input_image,
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outputs=[output_image, filepath, download_btn],
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show_progress="full"
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)
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# Handle download button click
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download_btn.click(
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fn=download_image,
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inputs=[filepath],
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outputs=[download_file]
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)
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# Add custom HTML for button styling enhancement
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gr.HTML("""
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<script>
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// This script will ensure buttons are properly styled after DOM updates
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document.addEventListener('DOMContentLoaded', function() {
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// Process might be needed to re-apply styles after Gradio updates the DOM
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const observer = new MutationObserver(function() {
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const buttons = document.querySelectorAll('.download-button');
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buttons.forEach(button => {
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button.style.backgroundColor = '#4CAF50';
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button.style.color = 'white';
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});
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});
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observer.observe(document.body, { childList: true, subtree: true });
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});
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</script>
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""")
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if __name__ == "__main__":
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demo.launch(share=False)
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import os
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import time
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import uuid
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# Load the pre-trained model
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print("Loading model...")
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# Background removal process
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def process(image, progress=gr.Progress()):
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if image is None:
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return None, None
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progress(0, desc="Starting processing...")
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output_array = np.array(new_im.convert("RGBA"))
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progress(1.0, desc="Done!")
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# Return both the image for display and the filepath for download
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return output_array, filepath
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# Gradio interface setup
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title = "Background Removal"
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examples = [['./input.jpg']]
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# Create HTML with custom CSS
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custom_css = """
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<style>
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.container {
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display: flex;
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flex-direction: row;
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width: 100%;
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}
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.column {
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flex: 1;
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padding: 10px;
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}
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.result-area {
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position: relative;
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}
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.download-btn {
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background-color: #4CAF50;
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color: white;
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border: none;
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padding: 10px 20px;
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text-align: center;
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text-decoration: none;
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display: inline-block;
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font-size: 16px;
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margin-top: 10px;
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border-radius: 4px;
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cursor: pointer;
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transition: background-color 0.3s;
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}
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.download-btn:hover {
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background-color: #45a049;
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}
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</style>
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"""
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# Create the Gradio interface with a simpler approach
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demo = gr.Interface(
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fn=process,
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inputs=gr.Image(type="numpy", label="Upload Image"),
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outputs=[
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gr.Image(type="numpy", label="Result"),
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gr.File(label="Download Processed Image")
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],
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examples=examples,
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title=title,
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description=description + custom_css,
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allow_flagging="never",
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theme=gr.themes.Default(
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primary_hue="green",
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secondary_hue="green",
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),
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css="""
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.gradio-container .footer {
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display: none !important;
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}
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/* Style the download button to look like our green button */
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.file-button {
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background-color: #4CAF50 !important;
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color: white !important;
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border: none !important;
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padding: 10px 20px !important;
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font-size: 16px !important;
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border-radius: 4px !important;
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margin-top: 10px !important;
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}
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.file-button:hover {
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background-color: #45a049 !important;
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}
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"""
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if __name__ == "__main__":
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demo.launch(share=False)
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