Upload app.py

app.py

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+# Gradio app for YOLOv3
+
+import numpy as np
+import gradio as gr
+from pytorch_grad_cam import GradCAM
+from pytorch_grad_cam.utils.image import show_cam_on_image
+from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
+from display import inference
+
+
+gr.Interface(
+    inference,
+    inputs=[
+        gr.Image(label="Input Image"),
+        gr.Slider(0, 1, value=0.5, label="IOU Threshold"),
+        gr.Slider(0, 1, value=0.4, label="Threshold"),
+        gr.Checkbox(label="Show Grad Cam"),
+        gr.Slider(0, 1, value=0.5, label="Opacity of GradCAM"),
+    ],
+    outputs=gr.Gallery(rows=2, columns=1),
+    title = '''YoloV3 on PASCAL VOC Dataset From Scratch
+               Classes - aeroplane, bicycle, bird,
+               boat, bottle, bus, car, cat, chair,
+               cow, diningtable, dog,horse, motorbike,
+               person, pottedplant, sheep, sofa,train, tvmonitor
+             '''
+    
+    ,examples=[
+       ["Examples/000001.jpg", 0.75, 0.75, True, 0.5],
+       ["Examples/000002.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000003.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000004.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000005.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000006.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000007.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000008.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000009.jpg", 0.75, 0.75, True, 0.5]
+       ["Examples/000010.jpg", 0.75, 0.75, True, 0.5]
+       ]
+      
+    ,
+    layout="horizontal"
+).launch(debug=True)