Update app.py

app.py

@@ -27,6 +27,7 @@ flickr = FlickrAPI(FLICKR_API_KEY, FLICKR_API_SECRET, format='parsed-json', stor
 
 def get_photo_id(url):
     """Extract photo ID from Flickr URL"""
+    """ex. get_photo_id(https://exemple.com/images/photo_chat_001.jpg)= photo"""
     try:
         return url.split('/')[-1].split('_')[0]
     except:
@@ -89,7 +90,7 @@ def calculate_rewards(subscription, num_generations, author_share, ro_share, num
     
     rewards = []
     for sim in similarities[0]:
-        # Attribution bonus based on similarity score and number of neighbors
+        # Attribution bonus based on similarity score (sim) and number of neighbors (len)
         attribution_bonus = sim * len(similarities[0])
         
         # Calculate monthly rewards
@@ -117,11 +118,11 @@ index = None
 urls = None
 
 def init_model():
-    global model, index, urls
-    model = load_model()
-    index = load_index("data/openimages_index.bin")
-    with open("data/openimages_urls.txt", "r") as f:
-        urls = f.readlines()
+    global model, index, urls                       #variables du script, et non de la seule fonction
+    model = load_model()                            #model charge DinoV2
+    index = load_index("data/openimages_index.bin") #index charge l'index binaire des vecteurs
+    with open("data/openimages_urls.txt", "r") as f:#ouvre le fichier texte des URLs
+        urls = f.readlines()                        #lit toutes les URLs
 
 @app.route('/')
 def home():
@@ -143,19 +144,23 @@ DEFAULT_PARAMS = {
 
 @app.route('/select_preset/<int:preset_id>')
 def select_preset(preset_id):
-    if preset_id not in PRESET_IMAGES:
+    if preset_id not in PRESET_IMAGES:        #vérification de l'existence de preset_id dans le dictionnaire
         return jsonify({'error': 'Invalid preset ID'}), 400
     
     try:
-        image_path = PRESET_IMAGES[preset_id]
+        image_path = PRESET_IMAGES[preset_id] #récupère le chemin du fichier image
         image = Image.open(image_path).convert('RGB')
         
         # Use default parameters for presets
         params = DEFAULT_PARAMS.copy()
         
         # Get features and search
-        features = get_ft(model, image)
+        features = get_ft(model, image)        #extrait les features, soit le vecteur représentant l’image
         distances, indices = get_topk(index, features, topk=params['num_neighbors'])
+                                               #utilise l’index pour trouver les k voisins de l’image
+                                               #retourne 
+                                               # - distances avec les voisins
+                                               # - indices : les positions (dans l'index) des voisins
         
         # Collect valid results first
         valid_results = []