def test_crop_yuv_out_of_bounds(self):
cropped = yuv_region_2_rgb(self.yuv_frame, (0, 0, 200, 200))
# cv2.imwrite(f"cropped.jpg", cv2.cvtColor(cropped, cv2.COLOR_RGB2BGR))
# ensure the upper left pixel is red
# the yuv conversion has some noise
assert np.all(cropped[0, 0] == [255, 1, 0])
# ensure the bottom right is black
assert np.all(cropped[199, 199] == [0, 0, 0])
def test_crop_yuv_portrait(self):
bgr_frame = np.zeros((1920, 1080, 3), np.uint8)
bgr_frame[:] = (0, 0, 255)
bgr_frame[5:55, 5:55] = (255, 0, 0)
# cv2.imwrite(f"bgr_frame.jpg", self.bgr_frame)
yuv_frame = cv2.cvtColor(bgr_frame, cv2.COLOR_BGR2YUV_I420)
cropped = yuv_region_2_rgb(yuv_frame, (0, 852, 648, 1500))
def create_tensor_input(frame, region):
cropped_frame = yuv_region_2_rgb(frame, region)
# Resize to 300x300 if needed
if cropped_frame.shape != (300, 300, 3):
cropped_frame = cv2.resize(cropped_frame, dsize=(300, 300), interpolation=cv2.INTER_LINEAR)
# Expand dimensions since the model expects images to have shape: [1, 300, 300, 3]
return np.expand_dims(cropped_frame, axis=0)
def test_crop_yuv(self):
cropped = yuv_region_2_rgb(self.yuv_frame, (10, 10, 50, 50))
# ensure the upper left pixel is blue
assert np.all(cropped[0, 0] == [0, 0, 255])
