impl

app.py

@@ -3,5 +3,42 @@ import gradio as gr
 def greet(name):
     return "Hello " + name + "!!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def predict(model, image, device):
+    pred_fun = torch.nn.Softmax(dim=1)
+    preds = []
+    with torch.set_grad_enabled(False):
+        x = image.to(device)
+        y = pred_fun(model(x))
+    y = y.cpu().numpy()
+    y = y[:, 1]  # cat:0, dog: 1
+    preds.append(y)
+    preds = np.concatenate(preds)
+    return preds
+
+def process_image(input_image, output_type):
+	model = torch.load('models/tenichi_noentry.pth')
+	preds = predict(model, input_image, 'cpu')
+	return preds
+
+
+iface = gr.Interface(
+    fn=process_image,
+    inputs=[
+        gr.Image(type="pil", label="Input Image", height=512),
+    ],
+    outputs=gr.Label(label="Output", show_label=False),
+    description="天下一品 or 進入禁止"
+    # examples=[
+    #     ["1.png", "Default"],
+    #     ["2.png", "Default"],
+    #     ["3.jfif", "Default"],
+    #     ["4.webp", "Default"]
+    # ],
+    # cache_examples=True
+)
+
+if __name__ == "__main__":
+    iface.launch()
+
+# demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+# demo.launch()