Add application file

app.py

@@ -5,9 +5,11 @@ import torch
 import torch.nn.functional as F
 import pandas as pd
 
-extractor = AutoImageProcessor.from_pretrained("mrm8488/resnet50-finetuned-trashnet")
-model = AutoModelForImageClassification.from_pretrained("mrm8488/resnet50-finetuned-trashnet")
+# Chargement du processeur et du modèle
+processor = AutoImageProcessor.from_pretrained("tribber93/my-trash-classification")
+model = AutoModelForImageClassification.from_pretrained("tribber93/my-trash-classification")
 
+# Dictionnaire de correspondance entre les labels et les types de poubelles
 POUBELLES = {
     "cardboard": "papier/carton",
     "glass": "verre",
@@ -17,8 +19,9 @@ POUBELLES = {
     "trash": "ordures ménagères",
 }
 
+# Fonction de classification de l'image
 def classify_image(image):
-    inputs = extractor(images=image, return_tensors="pt")
+    inputs = processor(images=image, return_tensors="pt")
     with torch.no_grad():
         logits = model(**inputs).logits
         probs = F.softmax(logits, dim=-1)
@@ -39,6 +42,7 @@ def classify_image(image):
 
     return pd.DataFrame(rows)
 
+# Création de l'interface Gradio
 gr.Interface(
     fn=classify_image,
     inputs=gr.Image(type="pil"),