Upload app.py

app.py

@@ -7,7 +7,7 @@ import torch
 import numpy as np
 
 # load model
-model_face = torch.load('face_model.pt')
+model_face = torch.load('face_model(1).pt')
 model_face.eval()
 model_plate = yolov5.load('keremberke/yolov5m-license-plate', device="cpu")
 # # set model parameters
@@ -25,7 +25,7 @@ def blur_plates_image(image, plate_blur):
     for box in boxes_plate_list:
         ROI = image[int(box[1]):int(box[3]), int(box[0]):int(box[2])]
 
-        blur_value = (plate_blur * 2 - 1)
+        blur_value = (int(plate_blur) * 2 - 1)
         blur = cv2.GaussianBlur(ROI, (blur_value, blur_value), 20, cv2.BORDER_DEFAULT)
         # Insert ROI back into image
         image[int(box[1]):int(box[3]), int(box[0]):int(box[2])] = blur
@@ -51,7 +51,7 @@ def blur_faces_image(image, face_blur):
         ROI = np.zeros(image.shape, dtype='uint8')
         cv2.circle(ROI, circle_center, circle_radius, (255, 255, 255), -1)
 
-        blur_value = (face_blur * 2 - 1)
+        blur_value = (int(face_blur) * 2 - 1)
         blur = cv2.GaussianBlur(image, (blur_value, blur_value), cv2.BORDER_DEFAULT)
 
         image = np.where(ROI > 0, blur, image)