Update app.py

app.py

@@ -1,11 +1,44 @@
 import gradio as gr
 import numpy as np
 
-def flip(im):
-    return np.flipud(im)
+from ultralyticsplus import YOLO, render_result
+import cv2
+from PIL import Image
+
+from cv2 import imshow
+from cv2 import imwrite
+
+
+#def flip(im):
+#    return np.flipud(im)
+
+def PPE(image):
+    # load model
+    #model = YOLO('keremberke/yolov8m-protective-equipment-detection')
+    model = YOLO('keremberke/yolov8m-hard-hat-detection')
+    # set model parameters
+    model.overrides['conf'] = 0.25  # NMS confidence threshold
+    model.overrides['iou'] = 0.45  # NMS IoU threshold
+    model.overrides['agnostic_nms'] = False  # NMS class-agnostic
+    model.overrides['max_det'] = 1000  # maximum number of detections per image
+
+
+
+    # perform inference
+    results = model.predict(image)
+
+    # observe results
+    print(results[0].boxes)
+    render = render_result(model=model, image=image, result=results[0])
+    render.show()
+
+
+
+
+
 
 demo = gr.Interface(
-    flip, 
+    PPE, 
     gr.Image(source="webcam", streaming=True), 
     "image",
     live=True