test

app.py

@@ -5,26 +5,24 @@ from supervision import Detections
 from PIL import Image
 import cv2
 import supervision as sv
+import gradio as gr
 
-# download model
 model_path = hf_hub_download(repo_id="arnabdhar/YOLOv8-Face-Detection", filename="model.pt")
 
 # load model
 model = YOLO(model_path)
 
-# inference
-image_path = "aespa.jpg"
-output = model(Image.open(image_path))
-results = Detections.from_ultralytics(output[0])
+def process_image(image):
 
-src = cv2.imread("aespa.jpg")
+    output = model(image)
+    results = Detections.from_ultralytics(output[0])
 
-bounding_box_annotator = sv.BoundingBoxAnnotator()
-annotated_frame = bounding_box_annotator.annotate(
-    scene = src.copy(),
-    detections = results
-)
+    bounding_box_annotator = sv.BoundingBoxAnnotator()
+    annotated_frame = bounding_box_annotator.annotate(
+        scene = image.copy(),
+        detections = results
+    )
+    return annotated_frame
 
-cv2.imshow("faces", annotated_frame)
-cv2.waitKey()
-cv2.destroyAllWindows()
+demo = gr.Interface(fn=process_image, inputs="image", outputs="image")
+demo.launch()   

requirements.txt

@@ -0,0 +1,4 @@
+opencv-python
+huggingface_hub
+ultralytics
+supervision