refactor: title

app.py

@@ -8,8 +8,8 @@ processor = CLIPProcessor.from_pretrained("tokenizer")
 
 def generate_answer(image):
 
-    clas = ['high_natural_light','neutral_natural_light','No_Light', 'artificial_lights']
-    classes = ['A picture of a room filled with abundant natural light with a lot windows, without objects that prevent the light from passing through regardless of whether it is night','A picture of a room with neutral natural light with few windows, without objects that prevent the light from passing through regardless of whether it is night','Nolights','A picture of a room with Artificial lights like lamps or headlamps']
+    classes = ['A picture of a room filled with abundant natural light with a lot or few windows regardless of whether it is night, without objects that prevent the light from passing through.','a picture of room in the dark','A picture of a living room with Artificial lights like lamps or headlamps']
+    clas = ['natural_light','no_light', 'artificial_light']
     inputs = processor(text=classes, images=image, return_tensors="pt", padding=True)
     outputs = model(**inputs)
     logits_per_image = outputs.logits_per_image