Update app.py

app.py

@@ -32,16 +32,16 @@ def palm_detection(image):
     # Generate a unique filename and save the annotated image
     unique_id = str(uuid.uuid4())
     filename = f"{unique_id}.jpg"
-    _, buffer = cv2.imencode('.jpg', annotated_frame)
-    binary_image = buffer.tobytes()
-    repo_name = get_full_repo_name(model_id="SawitDetection", token=hf_token)
-    img_file_url = upload_file(
-        path_or_fileobj=binary_image,
-        path_in_repo=filename,
-        repo_id=repo_name,
-        repo_type="space",
-        token=hf_token,
-    )
+    #_, buffer = cv2.imencode('.jpg', annotated_frame)
+    #binary_image = buffer.tobytes()
+    #repo_name = get_full_repo_name(model_id="SawitDetection", token=hf_token)
+    #img_file_url = upload_file(
+        #path_or_fileobj=binary_image,
+        #path_in_repo=filename,
+        #repo_id=repo_name,
+        #repo_type="space",
+        #token=hf_token,
+   # )
 
     # Append the results to the list
     results_list.append({
@@ -54,14 +54,14 @@ def palm_detection(image):
     results_df = pd.DataFrame(results_list)
     csv_filename = 'detection_results.csv'
     csv_output_path = os.path.join(csv_filename)
-    results_df.to_csv(csv_output_path, index=False)
-    csv_file_url = upload_file(
-        path_or_fileobj=csv_output_path,
-        path_in_repo=csv_filename,
-        repo_id=repo_name,
-        repo_type="space",
-        token=hf_token,
-    )
+    #results_df.to_csv(csv_output_path, index=False)
+    #csv_file_url = upload_file(
+       # path_or_fileobj=csv_output_path,
+       # path_in_repo=csv_filename,
+       # repo_id=repo_name,
+       # repo_type="space",
+       # token=hf_token,
+   # )
     return annotated_frame, results_df
     
 with gr.Blocks(theme = "soft", title="Palm Detector") as palm_detector: