modify app

app.py

@@ -5,12 +5,9 @@ import yolov5
 import cv2
 import torch
 import numpy as np
-from models.experimental import attempt_load
 
 # load model
-#model_face = torch.hub.load('.', 'custom', '/home/gmarti/Documentos/detection/yolov5s-face.pt', source='local', force_reload=True).to("cpu")
-#torch.save(model_face, 'face_model.pt')
-model_face = torch.load('/home/gmarti/Documentos/detection/face_model.pt')
+model_face = torch.load('face_model.pt')
 model_face.eval()
 model_plate = yolov5.load('keremberke/yolov5m-license-plate', device="cpu")
 # # set model parameters
@@ -21,13 +18,6 @@ model_plate.multi_label = False  # NMS multiple labels per box
 model_plate.max_det = 1000  # maximum number of detections per image
 
 
-#model = torch.hub.load('.', 'yolov5s','/home/gmarti/Documentos/detection/yolov5s-face.pt', 'yolov5s', device='cpu', source='local')
-
-#model_face = torch.load('/home/gmarti/Documentos/detection/yolov5s-face.pt', map_location=torch.device("cpu"))
-#model_face = attempt_load('/home/gmarti/Documentos/detection/yolov5s-face.pt', map_location=torch.device("cpu"))
-#model_face.to(torch.device("cpu"))
-
-
 def blur_plates_image(image, plate_blur):
 
     results_plate = model_plate(image, augment=True)
@@ -46,7 +36,6 @@ def blur_plates_image(image, plate_blur):
 def blur_faces_image(image, face_blur):
 
     results = model_face(np.array(image))
-    #results = model_face(torch.from_numpy(image))
 
     # parse results
     boxes_face_list = results.pred[0][:, :4].cpu().numpy().tolist() # x1, y1, x2, y2