Files
FastDeploy/tests/models/test_ppliteseg.py
huangjianhui 312e1b097d [Other]Refactor PaddleSeg with preprocessor && postprocessor && support batch (#639)
* Refactor PaddleSeg with preprocessor && postprocessor

* Fix bugs

* Delete redundancy code

* Modify by comments

* Refactor according to comments

* Add batch evaluation

* Add single test script

* Add ppliteseg single test script && fix eval(raise) error

* fix bug

* Fix evaluation segmentation.py batch predict

* Fix segmentation evaluation bug

* Fix evaluation segmentation bugs

Co-authored-by: Jason <jiangjiajun@baidu.com>
2022-11-28 15:50:12 +08:00

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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import fastdeploy as fd
from fastdeploy import ModelFormat
import cv2
import os
import numpy as np
import runtime_config as rc
import pickle
def test_segmentation_ppliteseg():
pp_liteseg_model_url = "https://bj.bcebos.com/fastdeploy/tests/PP_LiteSeg_T_STDC1_cityscapes_without_argmax_test.tgz"
fd.download_and_decompress(pp_liteseg_model_url, "resources")
model_path = "./resources/PP_LiteSeg_T_STDC1_cityscapes_without_argmax_test"
# 配置runtime加载模型
runtime_option = fd.RuntimeOption()
model_file = os.path.join(model_path, "model.pdmodel")
params_file = os.path.join(model_path, "model.pdiparams")
config_file = os.path.join(model_path, "deploy.yaml")
image_file_1 = os.path.join(model_path, "cityscapes_demo_1.png")
image_file_2 = os.path.join(model_path, "cityscapes_demo_2.png")
result_file_1 = os.path.join(model_path, "ppliteseg_result1.pkl")
result_file_2 = os.path.join(model_path, "ppliteseg_result2.pkl")
model = fd.vision.segmentation.PaddleSegModel(
model_file, params_file, config_file, runtime_option=rc.test_option)
model.postprocessor.store_score_map = True
im1 = cv2.imread(image_file_1)
im2 = cv2.imread(image_file_2)
with open(result_file_1, "rb") as f:
expect1 = pickle.load(f)
with open(result_file_2, "rb") as f:
expect2 = pickle.load(f)
for i in range(3):
# test single predict
result1 = model.predict(im1)
result2 = model.predict(im2)
diff_label_map_1 = np.fabs(
np.array(result1.label_map) - np.array(expect1["label_map"]))
diff_label_map_2 = np.fabs(
np.array(result2.label_map) - np.array(expect2["label_map"]))
diff_score_map_1 = np.fabs(
np.array(result1.score_map) - np.array(expect1["score_map"]))
diff_score_map_2 = np.fabs(
np.array(result2.score_map) - np.array(expect2["score_map"]))
thres = 1e-05
assert diff_label_map_1.max(
) < thres, "The label_map diff is %f, which is bigger than %f" % (
diff_label_map_1.max(), thres)
assert diff_score_map_1.max(
) < thres, "The score map diff is %f, which is bigger than %f" % (
diff_score_map_1.max(), thres)
assert diff_label_map_2.max(
) < thres, "The label_map diff is %f, which is bigger than %f" % (
diff_label_map_2.max(), thres)
assert diff_score_map_2.max(
) < thres, "The score map diff is %f, which is bigger than %f" % (
diff_score_map_2.max(), thres)
print("Single image No diff")
# test batch predict
results = model.batch_predict([im1, im2])
result1 = results[0]
result2 = results[1]
diff_label_map_1 = np.fabs(
np.array(result1.label_map) - np.array(expect1["label_map"]))
diff_label_map_2 = np.fabs(
np.array(result2.label_map) - np.array(expect2["label_map"]))
diff_score_map_1 = np.fabs(
np.array(result1.score_map) - np.array(expect1["score_map"]))
diff_score_map_2 = np.fabs(
np.array(result2.score_map) - np.array(expect2["score_map"]))
thres = 1e-05
assert diff_label_map_1.max(
) < thres, "The label_map diff is %f, which is bigger than %f" % (
diff_label_map_1.max(), thres)
assert diff_score_map_1.max(
) < thres, "The score map diff is %f, which is bigger than %f" % (
diff_score_map_1.max(), thres)
assert diff_label_map_2.max(
) < thres, "The label_map diff is %f, which is bigger than %f" % (
diff_label_map_2.max(), thres)
assert diff_score_map_2.max(
) < thres, "The score map diff is %f, which is bigger than %f" % (
diff_score_map_2.max(), thres)
print("Batch images No diff")
def test_segmentation_ppliteseg_runtime():
pp_liteseg_model_url = "https://bj.bcebos.com/fastdeploy/tests/PP_LiteSeg_T_STDC1_cityscapes_without_argmax_test.tgz"
fd.download_and_decompress(pp_liteseg_model_url, "resources")
model_path = "./resources/PP_LiteSeg_T_STDC1_cityscapes_without_argmax_test"
# 配置runtime加载模型
runtime_option = fd.RuntimeOption()
model_file = os.path.join(model_path, "model.pdmodel")
params_file = os.path.join(model_path, "model.pdiparams")
config_file = os.path.join(model_path, "deploy.yaml")
image_file_1 = os.path.join(model_path, "cityscapes_demo_1.png")
result_file_1 = os.path.join(model_path, "ppliteseg_result1.pkl")
preprocessor = fd.vision.segmentation.PaddleSegPreprocessor(config_file)
postprocessor = fd.vision.segmentation.PaddleSegPostprocessor(config_file)
postprocessor.store_score_map = True
rc.test_option.set_model_path(
model_file, params_file, model_format=ModelFormat.PADDLE)
rc.test_option.use_paddle_backend()
runtime = fd.Runtime(rc.test_option)
with open(result_file_1, "rb") as f:
expect1 = pickle.load(f)
im1 = cv2.imread(image_file_1)
print(image_file_1)
for i in range(3):
# test runtime
input_tensors, ims_info = preprocessor.run([im1])
output_tensors = runtime.infer({"x": input_tensors[0]})
results = postprocessor.run(output_tensors, ims_info)
result1 = results[0]
diff_label_map_1 = np.fabs(
np.array(result1.label_map) - np.array(expect1["label_map"]))
diff_score_map_1 = np.fabs(
np.array(result1.score_map) - np.array(expect1["score_map"]))
thres = 1e-05
assert diff_label_map_1.max(
) < thres, "The label_map diff is %f, which is bigger than %f" % (
diff_label_map_1.max(), thres)
assert diff_score_map_1.max(
) < thres, "The score map diff is %f, which is bigger than %f" % (
diff_score_map_1.max(), thres)
print("Runtime images No diff")
if __name__ == "__main__":
test_segmentation_ppliteseg()
test_segmentation_ppliteseg_runtime()