updates

app.py

@@ -20,8 +20,6 @@ dataset_name = "GeorgeIbrahim/EGYCOCO"  # Replace with your dataset name
 with open('nearest_neighbors_with_captions.json', 'r') as f:
     results = json.load(f)
 
-print(results)
-
 # Load or create the dataset
 try:
     dataset = load_dataset(dataset_name, split="train")
@@ -31,8 +29,6 @@ try:
     # Check if the 'split' column exists; if not, add it
     if 'split' not in dataset.column_names:
         # Define the 'split' values based on `image_id`
-        print(results)
-        print(example["image_id"] in results)
         split_values = [
             "dev" if example["image_id"] in results else "train" 
             for example in dataset
@@ -133,7 +129,6 @@ def get_next_image(session_data):
 
         # Iterate over each image file to apply the filtering logic
         for img in image_files:
-            print(img)  # Debugging line to print each image filename
 
             # Match and extract the image_id from the filename
             match = re.search(r'_(\d+)\.', img)
@@ -204,7 +199,7 @@ def save_annotation(caption, session_data):
 
         # # Clear user's current image if the validation image has been annotated twice
         # if (split == "train" and annotation_count > 1) or (split == "dev" and annotation_count > 2):
-        #     session_data["current_image"] = None
+        session_data["current_image"] = None
 
     # Fetch the next image
     next_image = get_next_image(session_data)