diff --git a/docs/examples/meter_reader.md b/docs/examples/meter_reader.md index 92658609825be255609001c73fba14c5f77f3d16..e410dd59e3a73f5ae0d0b0647c84629abf312863 100644 --- a/docs/examples/meter_reader.md +++ b/docs/examples/meter_reader.md @@ -179,7 +179,7 @@ git clone https://github.com/PaddlePaddle/PaddleX .\paddlex_inference\meter_reader.exe --det_model_dir=\path\to\encrypted_det_inference_model --seg_model_dir=\path\to\encrypted_seg_inference_model --image=\path\to\test.jpg --use_gpu=1 --use_erode=1 --save_dir=output --det_key yEBLDiBOdlj+5EsNNrABhfDuQGkdcreYcHcncqwdbx0= --seg_key DbVS64I9pFRo5XmQ8MNV2kSGsfEr4FKA6OH9OUhRrsY= ``` -### Linux系统的jeton嵌入式设备安全部署 +### Linux系统的jetson嵌入式设备安全部署 #### c++部署 diff --git a/examples/meter_reader/README.md b/examples/meter_reader/README.md index 55a969bd96afdbeaf70321f0c846a5598e8a72b5..37beef50d1d1e09ec0bd97cebd241a5484e0a9be 100644 --- a/examples/meter_reader/README.md +++ b/examples/meter_reader/README.md @@ -188,7 +188,7 @@ git clone https://github.com/PaddlePaddle/PaddleX .\paddlex_inference\meter_reader.exe --det_model_dir=\path\to\encrypted_det_inference_model --seg_model_dir=\path\to\encrypted_seg_inference_model --image=\path\to\test.jpg --use_gpu=1 --use_erode=1 --save_dir=output --det_key yEBLDiBOdlj+5EsNNrABhfDuQGkdcreYcHcncqwdbx0= --seg_key DbVS64I9pFRo5XmQ8MNV2kSGsfEr4FKA6OH9OUhRrsY= ``` -### Linux系统的jeton嵌入式设备安全部署 +### Linux系统的jetson嵌入式设备安全部署 #### c++部署 diff --git a/examples/meter_reader/deploy/python/reader_deploy.py b/examples/meter_reader/deploy/python/reader_deploy.py index 1cdb89cbfb8b1de84a4ffeda5beab0f74db8c10e..a5f5d18b0edad902217b6392cfc53dfb4709daf9 100644 --- a/examples/meter_reader/deploy/python/reader_deploy.py +++ b/examples/meter_reader/deploy/python/reader_deploy.py @@ -335,7 +335,7 @@ def infer(args): meter_reader.predict(im_file, args.save_dir, args.use_erode, args.erode_kernel, args.score_threshold, args.seg_batch_size, args.seg_thread_num) - elif args.with_camera: + elif args.use_camera: cap_video = cv2.VideoCapture(args.camera_id) if not cap_video.isOpened(): raise Exception( diff --git a/examples/meter_reader/reader_infer.py b/examples/meter_reader/reader_infer.py index 8a4cc324b6decb2d0842a7453ce5ef60bef9e8f6..c7f7d7367a7ef3d0b6bba4fd1c6a3258cd5145ac 100644 --- a/examples/meter_reader/reader_infer.py +++ b/examples/meter_reader/reader_infer.py @@ -335,7 +335,7 @@ def infer(args): meter_reader.predict(im_file, args.save_dir, args.use_erode, args.erode_kernel, args.score_threshold, args.seg_batch_size, args.seg_thread_num) - elif args.with_camera: + elif args.use_camera: cap_video = cv2.VideoCapture(args.camera_id) if not cap_video.isOpened(): raise Exception( diff --git a/examples/meter_reader/train_detection.py b/examples/meter_reader/train_detection.py index e29099c64506211db38e269267100847b9c4cb46..8a54361f19ff73ea3ce34d8df25c940b0e1308f3 100644 --- a/examples/meter_reader/train_detection.py +++ b/examples/meter_reader/train_detection.py @@ -6,7 +6,7 @@ from paddlex.det import transforms import paddlex as pdx # 下载和解压表计检测数据集 -meter_det_dataset = 'https://bj.bcebos.com/paddlex/meterreader/datasets/meter_det.tar.gz' +meter_det_dataset = 'https://bj.bcebos.com/paddlex/examples/meter_reader/datasets/meter_det.tar.gz' pdx.utils.download_and_decompress(meter_det_dataset, path='./') # 定义训练和验证时的transforms diff --git a/examples/meter_reader/train_segmentation.py b/examples/meter_reader/train_segmentation.py index 5ddae9554bcf3b12386de07c1766becf63db3cdf..a2f7e3b81ba97f585c7c80c2fa585fdcf3e1a222 100644 --- a/examples/meter_reader/train_segmentation.py +++ b/examples/meter_reader/train_segmentation.py @@ -6,7 +6,7 @@ import paddlex as pdx from paddlex.seg import transforms # 下载和解压表盘分割数据集 -meter_seg_dataset = 'https://bj.bcebos.com/paddlex/meterreader/datasets/meter_seg.tar.gz' +meter_seg_dataset = 'https://bj.bcebos.com/paddlex/examples/meter_reader/datasets/meter_seg.tar.gz' pdx.utils.download_and_decompress(meter_seg_dataset, path='./') # 定义训练和验证时的transforms @@ -42,8 +42,7 @@ eval_dataset = pdx.datasets.SegDataset( # # API说明: https://paddlex.readthedocs.io/zh_CN/latest/apis/models/semantic_segmentation.html#deeplabv3p model = pdx.seg.DeepLabv3p( - num_classes=len(train_dataset.labels), - backbone='Xception65') + num_classes=len(train_dataset.labels), backbone='Xception65') model.train( num_epochs=20, train_dataset=train_dataset,