Create app.py

app.py

@@ -0,0 +1,26 @@
+import torch
+import gradio as gr
+from transformers import pipeline
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+def predict(image, labels):
+    classifier = pipeline(task="image-classification")
+    inputs = classifier(image)
+    preds = [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds]
+    return preds
+
+description = """
+"""
+
+gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.inputs.Image(label="Image to classify", type="pil"),
+        # gr.inputs.Textbox(lines=1, label="Comma separated candidate labels", placeholder="Enter labels separated by ', '",)
+    ],
+    theme="grass",
+    outputs="label",
+    title="Comparateur d'image",
+    description=description
+).launch()