def load_normalized_test_case(data_paths, mean): case_num = randint(0, 9) [test_case_path] = common.locate_files(data_paths, [str(case_num) + ".pgm"]) # Flatten the image into a 1D array, and normalize. img = np.array(Image.open(test_case_path)).ravel() - mean return img, case_num
def load_normalized_test_case(data_paths, pagelocked_buffer, case_num=randint(0, 9)): [test_case_path] = common.locate_files(data_paths, [str(case_num) + ".pgm"]) # Flatten the image into a 1D array, normalize, and copy to pagelocked memory. img = np.array(Image.open(test_case_path)).ravel() np.copyto(pagelocked_buffer, 1.0 - img / 255.0) return case_num
def load_normalized_test_case(data_paths, pagelocked_buffer, case_num=randint(0, 9)): [test_case_path] = common.locate_files( data_paths, [str(case_num) + ".pgm"], err_msg= "MNIST image data not found. Please follow the README instructions.") # Flatten the image into a 1D array, normalize, and copy to pagelocked memory. img = np.array(Image.open(test_case_path)).ravel() np.copyto(pagelocked_buffer, 1.0 - img / 255.0) return case_num
def load_normalized_test_case(data_paths, pagelocked_buffer, case_num=randint(0, 9)): [test_case_path] = common.locate_files( data_paths, [str(case_num) + ".pgm"], err_msg= "Please follow the README in the mnist data directory (usually in `/usr/src/tensorrt/data/mnist`) to download the MNIST dataset" ) # Flatten the image into a 1D array, normalize, and copy to pagelocked memory. img = np.array(Image.open(test_case_path)).ravel() np.copyto(pagelocked_buffer, 1.0 - img / 255.0) return case_num
def load_normalized_test_case(data_paths, pagelocked_buffer, case_num=randint(0, 9)): #获取相应的测试数据路径的列表 [test_case_path] = common.locate_files( data_paths, [str(case_num) + ".pgm"], err_msg= "MNIST image data not found. Please follow the README instructions.") # Flatten the image into a 1D array, normalize, and copy to pagelocked memory. #ravel将图片多维数据降成一维 img = np.array(Image.open(test_case_path)).ravel() #对图片数据进行归一化并且复制到指定的页面锁定内存中 #numpy.copyto将相应的数据复制到提供的页面锁定内存中 np.copyto(pagelocked_buffer, 1.0 - img / 255.0) return case_num