RetinaFace test

RetinaFace/test.py

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+import cv2
+import sys
+import numpy as np
+import datetime
+import os
+import glob
+from retinaface import RetinaFace
+
+thresh = 0.8
+scales = [1024, 1980]
+
+count = 1
+
+gpuid = 0
+detector = RetinaFace('./model/R50', 0, gpuid, 'net3')
+
+img = cv2.imread('t1.jpg')
+print(img.shape)
+im_shape = img.shape
+target_size = scales[0]
+max_size = scales[1]
+im_size_min = np.min(im_shape[0:2])
+im_size_max = np.max(im_shape[0:2])
+#im_scale = 1.0
+#if im_size_min>target_size or im_size_max>max_size:
+im_scale = float(target_size) / float(im_size_min)
+# prevent bigger axis from being more than max_size:
+if np.round(im_scale * im_size_max) > max_size:
+    im_scale = float(max_size) / float(im_size_max)
+
+print('im_scale', im_scale)
+
+scales = [im_scale]
+flip = False
+
+for c in range(count):
+  faces, landmarks = detector.detect(img, thresh, scales=scales, do_flip=flip)
+  print(c, faces.shape, landmarks.shape)
+
+if faces is not None:
+  print('find', faces.shape[0], 'faces')
+  for i in range(faces.shape[0]):
+    #print('score', faces[i][4])
+    box = faces[i].astype(np.int)
+    #color = (255,0,0)
+    color = (0,0,255)
+    cv2.rectangle(img, (box[0], box[1]), (box[2], box[3]), color, 2)
+    if landmarks is not None:
+      landmark5 = landmarks[i].astype(np.int)
+      #print(landmark.shape)
+      for l in range(landmark5.shape[0]):
+        color = (0,0,255)
+        if l==0 or l==3:
+          color = (0,255,0)
+        cv2.circle(img, (landmark5[l][0], landmark5[l][1]), 1, color, 2)
+
+  filename = './detector_test.jpg'
+  print('writing', filename)
+  cv2.imwrite(filename, img)
+