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app.py

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+import argparse
+
+import numpy as np
+import torch
+import gradio
+
+import gradio as gr
+
+def object_detection(image):
+    image = image.convert("RGB")
+    image = image.resize((416, 416))
+    image = np.array(image).transpose((2, 0, 1))
+    image = np.expand_dims(image, axis=0).astype(np.float32)
+
+    # Run the model
+    outputs = session.run([output_name], {input_name: image})
+
+    # Postprocess the prediction
+    prediction = outputs[0][0]
+
+    return prediction
+
+
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        image_input=gr.Image()
+        image_output=gr.Image()
+        image_text =gr.Text()
+    image_button=gr.Button('start')
+
+    image_button.click(object_detection,inputs=image_input,outputs=[image_output,image_text])
+demo.close()
+demo.launch(server_port=9090)

epoch_124.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d3e17cb882b10313c8db2c1be2cb9ee4a8e26771ba76ff81f85850a37b919dbe
+size 298520114