wip

app.py

@@ -1,7 +1,22 @@
 import gradio as gr
+import torch
+from PIL import Image
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load a pretrained model (YOLOv5 for example)
+model = torch.hub.load("ultralytics/yolov5", "yolov5s", pretrained=True)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def detect_objects(image):
+    results = model(image)
+    detections = results.pandas().xyxy[0].to_dict(orient="records")
+    return detections  # JSON-friendly list of dicts
+
+# Gradio interface
+iface = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.JSON(),
+    examples=[]
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

@@ -0,0 +1,4 @@
+torch
+pillow
+gradio
+pandas