Update app.py

app.py

@@ -201,7 +201,6 @@ def generate_pdf(accuracy, roc_score, report_html, confusion_matrix_plot):
     buffer = BytesIO()
     c = canvas.Canvas(buffer, pagesize=letter)
     
-    # Add content to PDF
     c.drawString(100, 750, f"Model Results")
     c.drawString(100, 730, f"Accuracy: {accuracy:.2f}")
     c.drawString(100, 710, f"ROC Score: {roc_score:.2f}")
@@ -214,7 +213,6 @@ def generate_pdf(accuracy, roc_score, report_html, confusion_matrix_plot):
         c.drawString(100, y_position, line.strip())
         y_position -= 20
 
-    # Save Confusion Matrix Plot as an Image and Add it to the PDF
     img_buffer = BytesIO()
     confusion_matrix_plot.savefig(img_buffer, format="png")
     img_buffer.seek(0)
@@ -224,6 +222,16 @@ def generate_pdf(accuracy, roc_score, report_html, confusion_matrix_plot):
     buffer.seek(0)
     return buffer
 
+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():
@@ -247,16 +255,15 @@ def create_gradio_interface():
                         output_label = gr.Label(label="Output")
 
             with gr.Tab("Batch Image Processing"):
-                with gr.Accordion("Upload Zip File (max 100MB)", open=False):
+                with gr.Accordion("Upload Zip File", 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
+                        file_count="single"
                     )
                     zip_process_btn = gr.Button("Process Zip", interactive=False)
 
-                with gr.Accordion("Upload Individual Files (for datasets over 100MB)", open=False):
+                with gr.Accordion("Upload Individual Files", open=False):
                     with gr.Row():
                         ai_files = gr.File(
                             label="Upload AI Images",
@@ -326,10 +333,10 @@ def create_gradio_interface():
 
         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  # Reset outputs
+                None, None, None, None, None,
+                gr.Button.update(interactive=False),
+                gr.Button.update(interactive=False),
+                None, None, None, None, None
             ]
 
         reset_btn.click(