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])