add app and packages

app.py

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+import gradio as gr
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from PIL import Image
+import torch
+
+extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")
+model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")
+
+POUBELLES = {
+    "banana": "biodéchets",
+    "plastic bottle": "plastique",
+    "can": "métal",
+    "apple": "biodéchets",
+    "paper towel": "papier",
+    "glass": "verre",
+}
+
+def classify_image(image):
+    inputs = extractor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        logits = model(**inputs).logits
+    predicted_class_idx = logits.argmax(-1).item()
+    label = model.config.id2label[predicted_class_idx]
+
+    poubelle = POUBELLES.get(label.lower(), "inconnue")
+    return f"{label} → {poubelle}"
+
+gr.Interface(fn=classify_image, inputs=gr.Image(type="pil"), outputs="text").launch()

requirements.txt

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+torch
+transformers
+gradio
+Pillow