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