Update gradio.app.py

gradio.app.py

@@ -2,32 +2,9 @@ import gradio as gr
 import subprocess
 import os
 
-# Function to execute yolov5s-tt100k and return the output image path
-def run_yolov5s_tt100k(input_image_path):
-    # Define the paths
-    executable_path = "./build/yolov5s-tt100k"
-    model_path = "./yolov5s_tt100k_opt_fp32.tmfile"
-    output_image_path = "yolov5s-tt100k.out.jpg"
+def run_yolov5s(image_filepath):
+    result = subprocess.run(["./yolov5s-tt100k", "-m", "./yolov5s_tt100k_opt_fp32.tmfile", "-i", image_filepath], capture_output=True, text=True)
+    return "yolov5s-tt100k.out.jpg", result.stdout
 
-    # Run the yolov5s-tt100k executable with the input image
-    subprocess.run([executable_path, "-m", model_path, "-i", input_image_path])
-
-    # Check if the output image was created
-    if os.path.exists(output_image_path):
-        return output_image_path
-    else:
-        raise FileNotFoundError("The output image was not found.")
-
-# Create a Gradio interface
-iface = gr.Interface(
-    fn=run_yolov5s_tt100k,
-    inputs=gr.components.Image(),
-    outputs=gr.components.Image(),
-    title="YOLOv5s-TT100K Object Detection",
-    description="Upload an image to run object detection using YOLOv5s-TT100K.",
-    flagging_dir="/tmp/flagged"  # Set a writable directory for flagging
-)
-
-# Run the Gradio app
-if __name__ == "__main__":
-    iface.launch()
+iface = gr.Interface(fn=run_yolov5s, inputs=gr.Image(type="filepath"), outputs=[gr.Image(type="filepath"), gr.Textbox()])
+iface.launch()