add following features: update dropdowns after each rank submission, save the results at the end of the form in the dataset hub

app.py

@@ -2,15 +2,18 @@ import gradio as gr
 import yaml
 import random
 import os
+import json
+from pathlib import Path
+from huggingface_hub import CommitScheduler
 
-from src.utils import load_words, save_results, load_image_and_saliency, load_example_images
+from src.utils import load_words, load_image_and_saliency, load_example_images
 from src.style import css
 from src.user import UserID
 
 def main():
     config = yaml.safe_load(open("config/config.yaml"))
     words = ['grad-cam', 'lime', 'sidu', 'rise']
-    options = ['1', '2', '3', '4']
+    options = ['-', '1', '2', '3', '4']
     class_names = config['dataset'][config['dataset']['name']]['class_names']
     data_dir = os.path.join(config['dataset']['path'], config['dataset']['name'])
 
@@ -22,11 +25,11 @@ def main():
         answers = gr.State([])
 
         with gr.Row():
-            target_img_label = gr.Markdown(f"### Target image: {class_names[user_state.value]}")
-            gr.Markdown("### Grad-cam")
-            gr.Markdown("### Lime")
-            gr.Markdown("### Sidu")
-            gr.Markdown("### Rise")
+            target_img_label = gr.Markdown(f"Target image: **{class_names[user_state.value]}**")
+            gr.Markdown("Grad-cam")
+            gr.Markdown("Lime")
+            gr.Markdown("Sidu")
+            gr.Markdown("Rise")
 
         with gr.Row():
             count = user_state if isinstance(user_state, int) else user_state.value
@@ -115,19 +118,34 @@ def main():
             submit_button = gr.Button("Submit", visible=(count != max_images-1))
             return submit_button, finish_button
 
-        def update_dropdowns(dropdowns):
-            dropdown1 = gr.Dropdown(choices=options, label="grad-cam")
-            dropdown2 = gr.Dropdown(choices=options, label="lime")
-            dropdown3 = gr.Dropdown(choices=options, label="sidu")
-            dropdown4 = gr.Dropdown(choices=options, label="rise")
-            return dropdown1, dropdown2, dropdown3, dropdown4
+        def update_dropdowns():
+            dp1 = gr.Dropdown(choices=options, value=options[0], label="grad-cam")
+            dp2 = gr.Dropdown(choices=options, value=options[0], label="lime")
+            dp3 = gr.Dropdown(choices=options, value=options[0], label="sidu")
+            dp4 = gr.Dropdown(choices=options, value=options[0], label="rise")
+            return dp1, dp2, dp3, dp4
 
         def redirect():
             pass
 
-        def register_answers(answers):
-            experiment_dir = config['results']['exp1_dir']
-            save_results( experiment_dir, answers)
+        def save_results(answers):
+            json_file_results = config['results']['exp1_dir']
+            JSON_DATASET_DIR = Path("json_dataset")
+            JSON_DATASET_DIR.mkdir(parents=True, exist_ok=True)
+            JSON_DATASET_PATH = JSON_DATASET_DIR / json_file_results
+            scheduler = CommitScheduler(
+                repo_id="results",
+                repo_type="dataset",
+                folder_path=JSON_DATASET_DIR,
+                path_in_repo="data",
+            )
+            with scheduler.lock:
+                user_id = time.time()
+                with JSON_DATASET_PATH.open("a") as f:
+                    json.dump({
+                        "user_id": user_id, 
+                        "answer": {i: answer[i] for i in range(len(answer))}
+                    }, f)
  
         def add_answer(dropdown1,dropdown2,dropdown3,dropdown4, answers):
             rank = [dropdown1,dropdown2,dropdown3,dropdown4]
@@ -156,14 +174,13 @@ def main():
             outputs={target_img, saliency_gradcam, saliency_lime, saliency_sidu, saliency_rise, img1, img2, img3, img4, img5, img6, img7, img8, img9, img10, img11, img12, img13, img14, img15, img16},
         ).then(
             update_dropdowns,
-            inputs={dropdown1, dropdown2, dropdown3, dropdown4},
             outputs={dropdown1, dropdown2, dropdown3, dropdown4}
         )
        
         finish_button.click(
             add_answer, inputs=[dropdown1, dropdown2, dropdown3, dropdown4, answers],outputs=answers
         ).then(
-            register_answers, inputs=answers
+            save_results, inputs=answers
         ).then(
             redirect, js="window.location = 'https://marcoparola.github.io/saliency-evaluation-app/end'")
 

src/utils.py

@@ -32,37 +32,9 @@ def load_words(idx):
     words = [f"word_{idx}_{i}" for i in range(20)]
     return words
 
-# Function to save results and increment global variable
-def save_results(experiment_dir, answers):
-    user_id = time.time()
-    folder = os.path.join(config['results']['save_dir'], experiment_dir, str(user_id))
-    if not os.path.exists(folder):
-        os.makedirs(folder)
 
-    # answers is a list of lists
-    for idx, answer in enumerate(answers):
-        filename = os.path.join(folder, f"results_{idx}.txt")
-        with open(filename, 'w') as f:
-            f.write("\n".join(answer))
 
-    # Upload the file to Hugging Face Hub
-    api = HfApi()
-    token = os.getenv("HUGGINGFACE_TOKEN")
-    #token = HfFolder.get_token()
-    
-    if not token:
-        print("Token not found. Please login to Hugging Face.")
-        return
-    
-    try:
-        api.upload_file(
-            path_or_fileobj=filename,
-            path_in_repo=filename,
-            repo_id=config["repo_id"],
-            repo_type="space",
-            token=token,
-            commit_message="Add results.txt"
-        )
-        print(f"File {filename} uploaded successfully to {config['repo_id']}.")
-    except Exception as e:
-        print(f"Failed to upload file: {e}")
+
+
+
+