Update app.py

app.py

@@ -6,7 +6,7 @@ import PIL.Image as Image
 import PIL.Image as Image
 from ultralytics import YOLO
 from huggingface_hub import hf_hub_download, HfApi
-
+import random
 global repo_id
 
 def download_models(model_id):
@@ -19,6 +19,9 @@ def get_model_filenames(repo_id, file_extension = ".pt"):
     model_filenames = [file for file in files if file.endswith(file_extension)]
     return model_filenames
 
+def random_color():
+    return tuple(random.randint(0, 255) for _ in range(3))
+
 repo_id = "atalaydenknalbant/asl-yolo-models"
 model_filenames = get_model_filenames(repo_id)
 print("Model filenames:", model_filenames)
@@ -37,10 +40,8 @@ def yolo_inference(image, model_id, conf_threshold, iou_threshold, max_detection
     model = YOLO(model_path)
     results = model(source=image, imgsz=640, iou=iou_threshold, conf=conf_threshold, verbose=False, max_det=max_detection)[0]
     
-    # Get the detections and convert them to the supervision Detections format
     detections = sv.Detections.from_ultralytics(results)
     
-    # Prepare the labels
     labels = [
         f"{category_dict[class_id]} {confidence:.2f}"
         for class_id, confidence in zip(detections.class_id, detections.confidence)