diff --git a/tests/eval_example/test_pfld.py b/tests/eval_example/test_pfld.py deleted file mode 100644 index 62156c785..000000000 --- a/tests/eval_example/test_pfld.py +++ /dev/null @@ -1,42 +0,0 @@ -# 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 -import cv2 -import os -import numpy as np - - -def test_facealignment_pfld(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/pfld-106-lite.onnx" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/facealign_input.png" - output_url = "https://bj.bcebos.com/paddlehub/fastdeploy/result_landmarks.npy" - fd.download(model_url, ".") - fd.download(input_url, ".") - fd.download(output_url, ".") - model_path = "pfld-106-lite.onnx" - # use ORT - runtime_option = fd.RuntimeOption() - runtime_option.use_ort_backend() - model = fd.vision.facealign.PFLD(model_path, runtime_option=runtime_option) - - # compare diff - im = cv2.imread("./facealign_input.png") - result = model.predict(im.copy()) - expect = np.load("./result_landmarks.npy") - - diff = np.fabs(np.array(result.landmarks) - expect) - thres = 1e-04 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) diff --git a/tests/eval_example/test_ppmatting.py b/tests/eval_example/test_ppmatting.py deleted file mode 100644 index f1f188385..000000000 --- a/tests/eval_example/test_ppmatting.py +++ /dev/null @@ -1,109 +0,0 @@ -# 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 -import cv2 -import os -import pickle -import numpy as np - - -def test_matting_ppmatting(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/PP-Matting-512.tgz" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/matting_input.jpg" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "./PP-Matting-512" - # 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") - model = fd.vision.matting.PPMatting( - model_file, params_file, config_file, runtime_option=runtime_option) - - # 预测图片抠图结果 - im = cv2.imread("./matting_input.jpg") - result = model.predict(im.copy()) - pkl_url = "https://bj.bcebos.com/fastdeploy/tests/ppmatting_result.pkl" - if pkl_url: - fd.download(pkl_url, ".") - with open("./ppmatting_result.pkl", "rb") as f: - baseline = pickle.load(f) - - diff = np.fabs(np.array(result.alpha) - np.array(baseline)) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) - - -def test_matting_ppmodnet(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/PPModnet_MobileNetV2.tgz" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/matting_input.jpg" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "./PPModnet_MobileNetV2" - # 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") - model = fd.vision.matting.PPMatting( - model_file, params_file, config_file, runtime_option=runtime_option) - - # 预测图片抠图结果 - im = cv2.imread("./matting_input.jpg") - result = model.predict(im.copy()) - - pkl_url = "https://bj.bcebos.com/fastdeploy/tests/ppmodnet_result.pkl" - if pkl_url: - fd.download(pkl_url, ".") - with open("./ppmodnet_result.pkl", "rb") as f: - baseline = pickle.load(f) - - diff = np.fabs(np.array(result.alpha) - np.array(baseline)) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) - - -def test_matting_pphumanmatting(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/PPHumanMatting.tgz" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/matting_input.jpg" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "./PPHumanMatting" - # 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") - model = fd.vision.matting.PPMatting( - model_file, params_file, config_file, runtime_option=runtime_option) - - # 预测图片抠图结果 - im = cv2.imread("./matting_input.jpg") - result = model.predict(im.copy()) - - pkl_url = "https://bj.bcebos.com/fastdeploy/tests/pphumanmatting_result.pkl" - if pkl_url: - fd.download(pkl_url, ".") - - with open("./pphumanmatting_result.pkl", "rb") as f: - baseline = pickle.load(f) - - diff = np.fabs(np.array(result.alpha) - np.array(baseline)) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) diff --git a/tests/eval_example/test_pptinypose.py b/tests/eval_example/test_pptinypose.py deleted file mode 100644 index 0da899293..000000000 --- a/tests/eval_example/test_pptinypose.py +++ /dev/null @@ -1,100 +0,0 @@ -# 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 -import cv2 -import os -import numpy as np - - -def test_keypointdetection_pptinypose(): - pp_tinypose_model_url = "https://bj.bcebos.com/fastdeploy/tests/PP_TinyPose_256x192_test.tgz" - fd.download_and_decompress(pp_tinypose_model_url, ".") - model_path = "./PP_TinyPose_256x192_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, "infer_cfg.yml") - image_file = os.path.join(model_path, "hrnet_demo.jpg") - baseline_file = os.path.join(model_path, "baseline.npy") - model = fd.vision.keypointdetection.PPTinyPose( - model_file, params_file, config_file, runtime_option=runtime_option) - - # 预测图片关键点 - im = cv2.imread(image_file) - result = model.predict(im) - result = np.concatenate( - (np.array(result.keypoints), np.array(result.scores)[:, np.newaxis]), - axis=1) - baseline = np.load(baseline_file) - diff = np.fabs(result - np.array(baseline)) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) - print("No diff") - - -def test_keypointdetection_det_keypoint_unite(): - det_keypoint_unite_model_url = "https://bj.bcebos.com/fastdeploy/tests/PicoDet_320x320_TinyPose_256x192_test.tgz" - fd.download_and_decompress(det_keypoint_unite_model_url, ".") - model_path = "./PicoDet_320x320_TinyPose_256x192_test" - # 配置runtime，加载模型 - runtime_option = fd.RuntimeOption() - tinypose_model_file = os.path.join( - model_path, "PP_TinyPose_256x192_infer/model.pdmodel") - tinypose_params_file = os.path.join( - model_path, "PP_TinyPose_256x192_infer/model.pdiparams") - tinypose_config_file = os.path.join( - model_path, "PP_TinyPose_256x192_infer/infer_cfg.yml") - picodet_model_file = os.path.join( - model_path, "PP_PicoDet_V2_S_Pedestrian_320x320_infer/model.pdmodel") - picodet_params_file = os.path.join( - model_path, "PP_PicoDet_V2_S_Pedestrian_320x320_infer/model.pdiparams") - picodet_config_file = os.path.join( - model_path, "PP_PicoDet_V2_S_Pedestrian_320x320_infer/infer_cfg.yml") - image_file = os.path.join(model_path, "000000018491.jpg") - # image_file = os.path.join(model_path, "hrnet_demo.jpg") - - baseline_file = os.path.join(model_path, "baseline.npy") - - tinypose_model = fd.vision.keypointdetection.PPTinyPose( - tinypose_model_file, - tinypose_params_file, - tinypose_config_file, - runtime_option=runtime_option) - - det_model = fd.vision.detection.PicoDet( - picodet_model_file, - picodet_params_file, - picodet_config_file, - runtime_option=runtime_option) - - # 预测图片关键点 - im = cv2.imread(image_file) - pipeline = fd.pipeline.PPTinyPose(det_model, tinypose_model) - pipeline.detection_model_score_threshold = 0.5 - result = pipeline.predict(im) - print(result) - result = np.concatenate( - (np.array(result.keypoints), np.array(result.scores)[:, np.newaxis]), - axis=1) - print(result) - np.save("baseline.npy", result) - baseline = np.load(baseline_file) - diff = np.fabs(result - np.array(baseline)) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) - print("No diff") diff --git a/tests/eval_example/test_pptracking.py b/tests/eval_example/test_pptracking.py deleted file mode 100644 index ee1cb9bc5..000000000 --- a/tests/eval_example/test_pptracking.py +++ /dev/null @@ -1,89 +0,0 @@ -# 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 -import cv2 -import os -import numpy as np -import pickle - - -def test_pptracking_cpu(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/pptracking.tgz" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/person.mp4" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "pptracking/fairmot_hrnetv2_w18_dlafpn_30e_576x320" - # use default backend - 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, "infer_cfg.yml") - model = fd.vision.tracking.PPTracking(model_file, params_file, config_file, runtime_option=runtime_option) - cap = cv2.VideoCapture("./person.mp4") - frame_id = 0 - while True: - _, frame = cap.read() - if frame is None: - break - result = model.predict(frame) - # compare diff - expect = pickle.load(open("pptracking/frame" + str(frame_id) + ".pkl", "rb")) - diff_boxes = np.fabs(np.array(expect["boxes"]) - np.array(result.boxes)) - diff_scores = np.fabs(np.array(expect["scores"]) - np.array(result.scores)) - diff = max(diff_boxes.max(), diff_scores.max()) - thres = 1e-05 - assert diff < thres, "The label diff is %f, which is bigger than %f" % (diff, thres) - frame_id = frame_id + 1 - cv2.waitKey(30) - if frame_id >= 10: - cap.release() - cv2.destroyAllWindows() - break - - -def test_pptracking_gpu(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/pptracking.tgz" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/person.mp4" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "pptracking/fairmot_hrnetv2_w18_dlafpn_30e_576x320" - runtime_option = fd.RuntimeOption() - runtime_option.use_gpu() - # Not supported trt backend, up to now - # runtime_option.use_trt_backend() - 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, "infer_cfg.yml") - model = fd.vision.tracking.PPTracking(model_file, params_file, config_file, runtime_option=runtime_option) - cap = cv2.VideoCapture("./person.mp4") - frame_id = 0 - while True: - _, frame = cap.read() - if frame is None: - break - result = model.predict(frame) - # compare diff - expect = pickle.load(open("pptracking/frame" + str(frame_id) + ".pkl", "rb")) - diff_boxes = np.fabs(np.array(expect["boxes"]) - np.array(result.boxes)) - diff_scores = np.fabs(np.array(expect["scores"]) - np.array(result.scores)) - diff = max(diff_boxes.max(), diff_scores.max()) - thres = 1e-05 - assert diff < thres, "The label diff is %f, which is bigger than %f" % (diff, thres) - frame_id = frame_id + 1 - cv2.waitKey(30) - if frame_id >= 10: - cap.release() - cv2.destroyAllWindows() - break diff --git a/tests/eval_example/test_quantize_diff.py b/tests/eval_example/test_quantize_diff.py deleted file mode 100755 index 8bc7b396a..000000000 --- a/tests/eval_example/test_quantize_diff.py +++ /dev/null @@ -1,96 +0,0 @@ -# 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 -import cv2 -import os -import pickle -import numpy as np - -model_url = "https://bj.bcebos.com/fastdeploy/tests/yolov6_quant.tgz" -fd.download_and_decompress(model_url, ".") - - -def test_quant_mkldnn(): - model_path = "./yolov6_quant" - model_file = os.path.join(model_path, "model.pdmodel") - params_file = os.path.join(model_path, "model.pdiparams") - - input_file = os.path.join(model_path, "input.npy") - output_file = os.path.join(model_path, "mkldnn_output.npy") - - option = fd.RuntimeOption() - option.use_paddle_backend() - option.use_cpu() - - option.set_model_path(model_file, params_file) - runtime = fd.Runtime(option) - input_name = runtime.get_input_info(0).name - data = np.load(input_file) - outs = runtime.infer({input_name: data}) - expected = np.load(output_file) - diff = np.fabs(outs[0] - expected) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) - - -def test_quant_ort(): - model_path = "./yolov6_quant" - model_file = os.path.join(model_path, "model.pdmodel") - params_file = os.path.join(model_path, "model.pdiparams") - - input_file = os.path.join(model_path, "input.npy") - output_file = os.path.join(model_path, "ort_output.npy") - - option = fd.RuntimeOption() - option.use_ort_backend() - option.use_cpu() - - option.set_ort_graph_opt_level(1) - - option.set_model_path(model_file, params_file) - runtime = fd.Runtime(option) - input_name = runtime.get_input_info(0).name - data = np.load(input_file) - outs = runtime.infer({input_name: data}) - expected = np.load(output_file) - diff = np.fabs(outs[0] - expected) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) - - -def test_quant_trt(): - model_path = "./yolov6_quant" - model_file = os.path.join(model_path, "model.pdmodel") - params_file = os.path.join(model_path, "model.pdiparams") - - input_file = os.path.join(model_path, "input.npy") - output_file = os.path.join(model_path, "trt_output.npy") - - option = fd.RuntimeOption() - option.use_trt_backend() - option.use_gpu() - - option.set_model_path(model_file, params_file) - runtime = fd.Runtime(option) - input_name = runtime.get_input_info(0).name - data = np.load(input_file) - outs = runtime.infer({input_name: data}) - expected = np.load(output_file) - diff = np.fabs(outs[0] - expected) - thres = 1e-05 - assert diff.max() < thres, "The diff is %f, which is bigger than %f" % ( - diff.max(), thres) diff --git a/tests/eval_example/test_rvm.py b/tests/eval_example/test_rvm.py deleted file mode 100644 index 4b8d5afe8..000000000 --- a/tests/eval_example/test_rvm.py +++ /dev/null @@ -1,101 +0,0 @@ -# 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 -import cv2 -import os -import pickle -import numpy as np - - -def test_matting_rvm_cpu(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/rvm.tgz" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/video.mp4" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "rvm/rvm_mobilenetv3_fp32.onnx" - # use ORT - runtime_option = fd.RuntimeOption() - runtime_option.use_ort_backend() - model = fd.vision.matting.RobustVideoMatting( - model_path, runtime_option=runtime_option) - - cap = cv2.VideoCapture(input_url) - - frame_id = 0 - while True: - _, frame = cap.read() - if frame is None: - break - result = model.predict(frame) - # compare diff - expect_alpha = np.load("rvm/result_alpha_" + str(frame_id) + ".npy") - result_alpha = np.array(result.alpha).reshape(1920, 1080) - diff = np.fabs(expect_alpha - result_alpha) - thres = 1e-05 - assert diff.max( - ) < thres, "The label diff is %f, which is bigger than %f" % ( - diff.max(), thres) - frame_id = frame_id + 1 - cv2.waitKey(30) - if frame_id >= 10: - cap.release() - cv2.destroyAllWindows() - break - - -def test_matting_rvm_gpu_trt(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/rvm.tgz" - input_url = "https://bj.bcebos.com/paddlehub/fastdeploy/video.mp4" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "rvm/rvm_mobilenetv3_trt.onnx" - # use TRT - runtime_option = fd.RuntimeOption() - runtime_option.use_gpu() - runtime_option.use_trt_backend() - runtime_option.set_trt_input_shape("src", [1, 3, 1920, 1080]) - runtime_option.set_trt_input_shape("r1i", [1, 1, 1, 1], [1, 16, 240, 135], - [1, 16, 240, 135]) - runtime_option.set_trt_input_shape("r2i", [1, 1, 1, 1], [1, 20, 120, 68], - [1, 20, 120, 68]) - runtime_option.set_trt_input_shape("r3i", [1, 1, 1, 1], [1, 40, 60, 34], - [1, 40, 60, 34]) - runtime_option.set_trt_input_shape("r4i", [1, 1, 1, 1], [1, 64, 30, 17], - [1, 64, 30, 17]) - model = fd.vision.matting.RobustVideoMatting( - model_path, runtime_option=runtime_option) - - cap = cv2.VideoCapture("./video.mp4") - - frame_id = 0 - while True: - _, frame = cap.read() - if frame is None: - break - result = model.predict(frame) - # compare diff - expect_alpha = np.load("rvm/result_alpha_" + str(frame_id) + ".npy") - result_alpha = np.array(result.alpha).reshape(1920, 1080) - diff = np.fabs(expect_alpha - result_alpha) - thres = 1e-04 - assert diff.max( - ) < thres, "The label diff is %f, which is bigger than %f" % ( - diff.max(), thres) - frame_id = frame_id + 1 - cv2.waitKey(30) - if frame_id >= 10: - cap.release() - cv2.destroyAllWindows() - break diff --git a/tests/eval_example/test_yolov5cls.py b/tests/eval_example/test_yolov5cls.py deleted file mode 100755 index 50eefa36c..000000000 --- a/tests/eval_example/test_yolov5cls.py +++ /dev/null @@ -1,49 +0,0 @@ -# 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 -import cv2 -import os -import pickle -import numpy as np - - -def test_classification_yolov5cls(): - model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov5n-cls.tgz" - input_url = "https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg" - fd.download_and_decompress(model_url, ".") - fd.download(input_url, ".") - model_path = "yolov5n-cls/yolov5n-cls.onnx" - # use ORT - runtime_option = fd.RuntimeOption() - runtime_option.use_ort_backend() - model = fd.vision.classification.YOLOv5Cls( - model_path, runtime_option=runtime_option) - - # compare diff - im = cv2.imread("./ILSVRC2012_val_00000010.jpeg") - result = model.predict(im.copy(), topk=5) - with open("yolov5n-cls/result.pkl", "rb") as f: - expect = pickle.load(f) - - diff_label = np.fabs( - np.array(result.label_ids) - np.array(expect["labels"])) - diff_score = np.fabs(np.array(result.scores) - np.array(expect["scores"])) - thres = 1e-05 - assert diff_label.max( - ) < thres, "The label diff is %f, which is bigger than %f" % ( - diff_label.max(), thres) - assert diff_score.max( - ) < thres, "The score diff is %f, which is bigger than %f" % ( - diff_score.max(), thres)