Update app.py

app.py

@@ -1,38 +1,4 @@
-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((640, 640))
-    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)import os
+import os
 import sys
 import argparse
 import time