Create app.py

app.py

@@ -0,0 +1,147 @@
+html += "<h3>False Negatives (Real images classified as AI):</h3>"
+    html += '<div class="image-grid">'
+    for img_name, img_data in false_negatives:
+        html += f'''
+        <div class="image-item">
+            <img src="data:image/jpeg;base64,{img_data}" alt="{img_name}">
+            <p>{img_name}</p>
+        </div>
+        '''
+    html += '</div>'
+
+    return html
+
+def load_url(url):
+    try:
+        urllib.request.urlretrieve(url, "temp_image.png")
+        image = Image.open("temp_image.png")
+        message = "Image Loaded"
+    except Exception as e:
+        image = None
+        message = f"Image not Found<br>Error: {e}"
+    return image, message
+
+detector = AIDetector()
+
+def create_gradio_interface():
+    with gr.Blocks() as app:
+        gr.Markdown("""<center><h1>AI Image Detector</h1></center>""")
+
+        with gr.Tabs():
+            with gr.Tab("Single Image Detection"):
+                with gr.Column():
+                    inp = gr.Image(type='pil')
+                    in_url = gr.Textbox(label="Image URL")
+                    with gr.Row():
+                        load_btn = gr.Button("Load URL")
+                        btn = gr.Button("Detect AI")
+                    message = gr.HTML()
+
+                with gr.Group():
+                    with gr.Box():
+                        gr.HTML(f"""<b>Testing on Model: <a href='https://huggingface.co/{MODEL_NAME}'>{MODEL_NAME}</a></b>""")
+                        output_html = gr.HTML()
+                        output_label = gr.Label(label="Output")
+
+            with gr.Tab("Batch Image Processing"):
+                with gr.Accordion("Upload Zip File (max 100MB)", open=False):
+                    zip_file = gr.File(
+                        label="Upload Zip (must contain 'real' and 'ai' folders)",
+                        file_types=[".zip"],
+                        file_count="single",
+                        max_file_size=100  # 100 MB limit
+                    )
+                    zip_process_btn = gr.Button("Process Zip", interactive=False)
+
+                with gr.Accordion("Upload Individual Files (for datasets over 100MB)", open=False):
+                    with gr.Row():
+                        ai_files = gr.File(
+                            label="Upload AI Images",
+                            file_types=["image"],
+                            file_count="multiple"
+                        )
+                        real_files = gr.File(
+                            label="Upload Real Images",
+                            file_types=["image"],
+                            file_count="multiple"
+                        )
+                    individual_process_btn = gr.Button("Process Individual Files", interactive=False)
+
+                with gr.Group():
+                    gr.Markdown(f"### Results for {MODEL_NAME}")
+                    output_acc = gr.Label(label="Accuracy")
+                    output_roc = gr.Label(label="ROC Score")
+                    output_report = gr.HTML(label="Classification Report")
+                    output_plots = gr.Plot(label="Confusion Matrix and ROC Curve")
+                    output_fp_fn = gr.HTML(label="False Positives and Negatives")
+                    
+                    # Add export button and PDF output
+                    export_btn = gr.Button("Export Results to PDF", variant="primary")
+                    pdf_output = gr.File(label="Downloaded PDF")
+
+                reset_btn = gr.Button("Reset")
+
+        load_btn.click(load_url, in_url, [inp, message])
+        btn.click(
+            lambda img: detector.predict(img),
+            inp,
+            [output_html, output_label]
+        )
+
+        def enable_zip_btn(file):
+            return gr.Button.update(interactive=file is not None)
+
+        def enable_individual_btn(ai_files, real_files):
+            return gr.Button.update(interactive=(ai_files is not None and real_files is not None))
+
+        zip_file.upload(enable_zip_btn, zip_file, zip_process_btn)
+        
+        ai_files.upload(enable_individual_btn, [ai_files, real_files], individual_process_btn)
+        real_files.upload(enable_individual_btn, [ai_files, real_files], individual_process_btn)
+
+        zip_process_btn.click(
+            process_zip,
+            zip_file,
+            [output_acc, output_roc, output_report, output_plots, output_fp_fn]
+        )
+
+        individual_process_btn.click(
+            process_files,
+            [ai_files, real_files],
+            [output_acc, output_roc, output_report, output_plots, output_fp_fn]
+        )
+
+        # Add export button click handler
+        export_btn.click(
+            export_to_pdf,
+            inputs=[output_acc, output_roc, output_report, output_plots, output_fp_fn],
+            outputs=pdf_output
+        )
+
+        def reset_interface():
+            return [
+                None, None, None, None, None,  # Reset inputs
+                gr.Button.update(interactive=False),  # Reset zip process button
+                gr.Button.update(interactive=False),  # Reset individual process button
+                None, None, None, None, None, None  # Reset outputs (including PDF)
+            ]
+
+        reset_btn.click(
+            reset_interface,
+            inputs=None,
+            outputs=[
+                zip_file, ai_files, real_files,
+                output_acc, output_roc, output_report, output_plots, output_fp_fn,
+                zip_process_btn, individual_process_btn, pdf_output
+            ]
+        )
+
+    return app
+
+if __name__ == "__main__":
+    app = create_gradio_interface()
+    app.launch(
+        show_api=False,
+        max_threads=24,
+        show_error=True
+    )