Upload app.py

app.py

@@ -0,0 +1,34 @@
+
+import gradio as gr
+import torch
+
+###############
+
+def yolov7_inference(
+    image: gr.inputs.Image = None,
+
+):
+
+    device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+    path = 'y7-prdef.pt'
+    model = torch.hub.load("WongKinYiu/yolov7","custom",f"{path}")
+
+    results = model([image], size=640)
+    return results.render()[0]
+        
+
+inputs = [
+    gr.inputs.Image(type="pil", label="Input Image"),
+]
+
+
+demo_app = gr.Interface(
+    fn=yolov7_inference,
+    inputs=inputs,
+    outputs=gr.outputs.Image(type="filepath", label="Output Image"),
+    title="Yolov7 | Jar lid product defects",
+    examples=['t1.JPG'],
+    cache_examples=True,
+)
+demo_app.launch(debug=True, enable_queue=True)
+