Test using pip library

app.py

@@ -1,8 +1,7 @@
 import gradio as gr
-import numpy as np
 import os
 import spaces
-import PIL.Image
+import yolov9
 
 from huggingface_hub import hf_hub_download
 
@@ -22,8 +21,19 @@ def yolov9_inference(img_path, model_id='YOLOv9-S_X_LOCO-converted.pt', img_size
     """
     
     model_path = download_models(model_id)
+    model = yolov9.load(model_path)
+    
+    # Set model parameters
+    model.conf = conf_thres
+    model.iou = iou_thres
+    
+    # Perform inference
+    results = model(img_path, size=img_size)
 
-    return np.array(PIL.Image.open(img_path))
+    # Optionally, show detection bounding boxes on image
+    output = results.render()
+    
+    return output[0]
 
 def download_models(model_id):
     hf_hub_download("KoniHD/LOCO-Detection", filename=f"{model_id}", local_dir=f"./",

requirements.txt

@@ -2,5 +2,4 @@
 # Usage: pip install -r requirements.txt
 
 huggingface_hub
-ultralytics
-numpy>=1.18.5
+yolov9pip==0.0.4