perchè un'altra televisione è impossibile.. viva lammerda

app.py

@@ -13,13 +13,12 @@ def main():
     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'])
-    id_generator = UserID()
 
     with gr.Blocks(theme=gr.themes.Glass(), css=css) as demo:
         # Main App Components
         title = gr.Markdown("# Saliency evaluation - experiment 1")
         user_state = gr.State(0)
-        user_id = gr.State(0)
+        #user_id = gr.State(load_global_variable())
         answers = gr.State([])
 
         with gr.Row():
@@ -122,17 +121,13 @@ def main():
             dropdown3 = gr.Dropdown(choices=options, label="sidu")
             dropdown4 = gr.Dropdown(choices=options, label="rise")
             return dropdown1, dropdown2, dropdown3, dropdown4
-        
-        def init(request: gr.Request):
-            user_id.value = id_generator.increment()
-            return user_id
 
         def redirect():
             pass
 
         def register_answers(answers):
             experiment_dir = config['results']['exp1_dir']
-            save_results(user_id.value, experiment_dir, answers)
+            save_results( experiment_dir, answers)
  
         def add_answer(dropdown1,dropdown2,dropdown3,dropdown4, answers):
             rank = [dropdown1,dropdown2,dropdown3,dropdown4]
@@ -172,8 +167,7 @@ def main():
         ).then(
             redirect, js="window.location = 'https://marcoparola.github.io/saliency-evaluation-app/end'")
 
-        demo.load(init, inputs=None, outputs=user_id)
-    
+        demo.load()
     demo.launch()
 
 if __name__ == "__main__":

config/config.yaml

@@ -15,7 +15,7 @@ dataset:
   name: intel_image
   path: data
   intel_image:
-    n_classes: 2
+    n_classes: 6
     class_names: ['BUILDING', 'FOREST', 'GLACIER', 'MOUNTAIN', 'SEA', 'STREET']
   imagenette:
     n_classes: 10

src/utils.py

@@ -3,6 +3,7 @@ import pandas as pd
 from huggingface_hub import HfApi, HfFolder
 import yaml
 import numpy as np
+import time
 
 config = yaml.safe_load(open("./config/config.yaml")) 
     
@@ -26,42 +27,28 @@ def load_example_images(class_idx, data_dir, max_images=16):
     images = [os.path.join(path, images[id]) for id in ids]
     return images
 
-
 # Function to load words based on global variable
 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(user_it, experiment_dir, answers):
-    folder = os.path.join(config['results']['save_dir'], experiment_dir, str(user_it))
-
-    # convert answers (list of list) to a pandas dataframe
-    df = pd.DataFrame(answers, columns=config['saliency_methods'])
+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)
-    df.to_csv(os.path.join(folder, 'results.csv'), index=False)
-    print(f"Results saved to {folder}", df)
-
-    '''
-    filename = "results.txt"
-    print('ooooooo', global_counter)
-    print(dropdowns)
-    str_dropdowns = str(dropdowns)
-    # remove the curly braces
-    dropdowns = str_dropdowns[1:-1]
-    # split by comma and select the number contained in the string
-    dropdowns = [r.split(":")[1].strip().replace("'", "") for r in dropdowns.split(",")]
 
-    str_dropdowns = "\n".join([str(r) for r in dropdowns])
-    with open(filename, 'w') as f:
-        f.write(str_dropdowns)
-    '''
+    # 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()
+    #token = HfFolder.get_token()
     
     if not token:
         print("Token not found. Please login to Hugging Face.")