Create app.py

app.py

@@ -0,0 +1,25 @@
+from transformers import pipeline
+import torch
+
+def select_model(model_name):
+    return pipeline("image-classification", model=model_name)
+
+def predict(image, model_name):
+    pipeline = select_model(model_name)
+    predicts = pipeline(image)
+    return image, {p["label"]: p["score"] for p in predicts}
+
+iface = gr.Interface(
+    predict,
+    inputs=[
+        gr.Image(label="Input", sources=["upload", "webcam"], type="pil"),
+        gr.Dropdown(label="Model Name", choices=["miittnnss/pet-classifier", "miittnnss/pet-classifier-v2"], value="miittnnss/pet-classifier-v2")
+    ],
+    outputs=[
+        gr.Image(label="Processed"),
+        gr.Label(label="Result")
+    ],
+    title="Pet Classifier"
+)
+
+iface.launch(debug=True)