From cb7e10277e1d69d780fd4cd53159edd96de6c197 Mon Sep 17 00:00:00 2001 From: Zeref996 <53218160+Zeref996@users.noreply.github.com> Date: Wed, 4 Jan 2023 17:42:51 +0800 Subject: [PATCH 1/6] Fix serving/scripts build.sh (#1053) * fix serving/scripts build.sh * Update build.sh support: ``` bash build.sh --docker_name=test ``` * Update build.sh Co-authored-by: heliqi <1101791222@qq.com> --- serving/scripts/build.sh | 40 +++++++++++++++++++++++++++++++++++++--- 1 file changed, 37 insertions(+), 3 deletions(-) diff --git a/serving/scripts/build.sh b/serving/scripts/build.sh index cfcb68b37..fa7c0aacb 100644 --- a/serving/scripts/build.sh +++ b/serving/scripts/build.sh @@ -12,7 +12,41 @@ # 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. -WITH_GPU=${1:-ON} + +ARGS=`getopt -a -o w:n:h:hs -l WITH_GPU:,docker_name:,http_proxy:,https_proxy: -- "$@"` + +eval set -- "${ARGS}" +echo "parse start" + +while true +do + case "$1" in + -w|--WITH_GPU) + WITH_GPU="$2" + shift;; + -n|--docker_name) + docker_name="$2" + shift;; + -h|--http_proxy) + http_proxy="$2" + shift;; + -hs|--https_proxy) + https_proxy="$2" + shift;; + --) + shift + break;; + esac +shift +done + +if [ -z $WITH_GPU ];then + WITH_GPU="ON" +fi + +if [ -z $docker_name ];then + docker_name="build_fd" +fi if [ $WITH_GPU == "ON" ]; then @@ -30,7 +64,7 @@ if [ ! -d "./TensorRT-8.4.1.5/" ]; then rm -rf TensorRT-8.4.1.5.Linux.x86_64-gnu.cuda-11.6.cudnn8.4.tar.gz fi -nvidia-docker run -i --rm --name build_fd \ +nvidia-docker run -i --rm --name ${docker_name} \ -v`pwd`/..:/workspace/fastdeploy \ -e "http_proxy=${http_proxy}" \ -e "https_proxy=${https_proxy}" \ @@ -68,7 +102,7 @@ else echo "start build FD CPU library" -docker run -i --rm --name build_fd \ +docker run -i --rm --name ${docker_name} \ -v`pwd`/..:/workspace/fastdeploy \ -e "http_proxy=${http_proxy}" \ -e "https_proxy=${https_proxy}" \ From 2eaf6151986b6650e9d0b4bf9d16fbe8e141e766 Mon Sep 17 00:00:00 2001 From: Jason Date: Thu, 5 Jan 2023 10:11:07 +0800 Subject: [PATCH 2/6] Update README.md --- examples/vision/matting/rvm/README.md | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/examples/vision/matting/rvm/README.md b/examples/vision/matting/rvm/README.md index 16f33aae4..fb030de2e 100755 --- a/examples/vision/matting/rvm/README.md +++ b/examples/vision/matting/rvm/README.md @@ -14,12 +14,10 @@ 为了方便开发者的测试，下面提供了RobustVideoMatting导出的各系列模型，开发者可直接下载使用。 -| 模型 | 参数大小 | 精度 | 备注 | -|:---------------------------------------------------------------- |:----- |:----- | :------ | -| [rvm_mobilenetv3_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_fp32.onnx) | 15MB | - | -| [rvm_resnet50_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_fp32.onnx) | 103MB | - | -| [rvm_mobilenetv3_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_trt.onnx) | 15MB | - | -| [rvm_resnet50_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_trt.onnx) | 103MB | - | +| [rvm_mobilenetv3_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_fp32.onnx) | 15MB ||此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | +| [rvm_resnet50_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_fp32.onnx) | 103MB | |此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | +| [rvm_mobilenetv3_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_trt.onnx) | 15MB | |此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | +| [rvm_resnet50_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_trt.onnx) | 103MB | | 此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | **Note**： - 如果要使用 TensorRT 进行推理，需要下载后缀为 trt 的 onnx 模型文件 From 3af011916b2e63926b0fc3edc4b41eb63fc4888e Mon Sep 17 00:00:00 2001 From: Jason Date: Thu, 5 Jan 2023 10:11:29 +0800 Subject: [PATCH 3/6] Update README.md --- examples/vision/matting/rvm/README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/examples/vision/matting/rvm/README.md b/examples/vision/matting/rvm/README.md index fb030de2e..93f0e2aab 100755 --- a/examples/vision/matting/rvm/README.md +++ b/examples/vision/matting/rvm/README.md @@ -14,6 +14,8 @@ 为了方便开发者的测试，下面提供了RobustVideoMatting导出的各系列模型，开发者可直接下载使用。 +| 模型 | 参数大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- | :------ | | [rvm_mobilenetv3_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_fp32.onnx) | 15MB ||此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | | [rvm_resnet50_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_fp32.onnx) | 103MB | |此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | | [rvm_mobilenetv3_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_trt.onnx) | 15MB | |此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | From ebbe2e055c1fdcbc60da91121a9a41f4e339ebc8 Mon Sep 17 00:00:00 2001 From: Jason Date: Thu, 5 Jan 2023 10:22:05 +0800 Subject: [PATCH 4/6] Update README.md --- examples/vision/matting/rvm/README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/examples/vision/matting/rvm/README.md b/examples/vision/matting/rvm/README.md index 93f0e2aab..56d371c5c 100755 --- a/examples/vision/matting/rvm/README.md +++ b/examples/vision/matting/rvm/README.md @@ -16,10 +16,10 @@ | 模型 | 参数大小 | 精度 | 备注 | |:---------------------------------------------------------------- |:----- |:----- | :------ | -| [rvm_mobilenetv3_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_fp32.onnx) | 15MB ||此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | -| [rvm_resnet50_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_fp32.onnx) | 103MB | |此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | -| [rvm_mobilenetv3_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_trt.onnx) | 15MB | |此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | -| [rvm_resnet50_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_trt.onnx) | 103MB | | 此模型文件来源于[RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | +| [rvm_mobilenetv3_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_fp32.onnx) | 15MB ||exported from [RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | +| [rvm_resnet50_fp32.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_fp32.onnx) | 103MB | |exported from [RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | +| [rvm_mobilenetv3_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_mobilenetv3_trt.onnx) | 15MB | |exported from [RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | +| [rvm_resnet50_trt.onnx](https://bj.bcebos.com/paddlehub/fastdeploy/rvm_resnet50_trt.onnx) | 103MB | | exported from [RobustVideoMatting](https://github.com/PeterL1n/RobustVideoMatting/commit/81a1093)，GPL-3.0 License | **Note**： - 如果要使用 TensorRT 进行推理，需要下载后缀为 trt 的 onnx 模型文件 From 9437c82848acf59b57d346c46894c085a5830511 Mon Sep 17 00:00:00 2001 From: WJJ1995 Date: Thu, 5 Jan 2023 13:24:24 +0800 Subject: [PATCH 5/6] [Model] GPL-3.0 License (#1062) * add GPL lisence * add GPL-3.0 lisence * add GPL-3.0 lisence * add GPL-3.0 lisence --- .../vision/detection/scaledyolov4/README.md | 25 +++++++++---------- examples/vision/detection/yolor/README.md | 25 +++++++++---------- examples/vision/detection/yolov5/README.md | 14 +++++------ .../vision/detection/yolov5lite/README.md | 12 ++++----- examples/vision/detection/yolov6/README.md | 13 +++++----- examples/vision/detection/yolov7/README.md | 18 ++++++------- examples/vision/detection/yolov7/README_EN.md | 16 ++++++------ .../detection/yolov7end2end_ort/README.md | 16 ++++++------ .../detection/yolov7end2end_trt/README.md | 16 ++++++------ 9 files changed, 75 insertions(+), 80 deletions(-) diff --git a/examples/vision/detection/scaledyolov4/README.md b/examples/vision/detection/scaledyolov4/README.md index 36ec1af0c..df3799282 100644 --- a/examples/vision/detection/scaledyolov4/README.md +++ b/examples/vision/detection/scaledyolov4/README.md @@ -23,19 +23,18 @@ ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了ScaledYOLOv4导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [ScaledYOLOv4-P5-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5-896.onnx) | 271MB | 51.2% | -| [ScaledYOLOv4-P5+BoF-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_-896.onnx) | 271MB | 51.7% | -| [ScaledYOLOv4-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6-1280.onnx) | 487MB | 53.9% | -| [ScaledYOLOv4-P6+BoF-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_-1280.onnx) | 487MB | 54.4% | -| [ScaledYOLOv4-P7-1536](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7-1536.onnx) | 1.1GB | 55.0% | -| [ScaledYOLOv4-P5](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5.onnx) | 271MB | - | -| [ScaledYOLOv4-P5+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_.onnx) | 271MB | -| -| [ScaledYOLOv4-P6](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6.onnx) | 487MB | - | -| [ScaledYOLOv4-P6+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_.onnx) | 487MB | - | -| [ScaledYOLOv4-P7](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7.onnx) | 1.1GB | - | - +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- |:----- | +| [ScaledYOLOv4-P5-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5-896.onnx) | 271MB | 51.2% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P5+BoF-896](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_-896.onnx) | 271MB | 51.7% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6-1280.onnx) | 487MB | 53.9% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P6+BoF-1280](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_-1280.onnx) | 487MB | 54.4% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P7-1536](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7-1536.onnx) | 1.1GB | 55.0% | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P5](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5.onnx) | 271MB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P5+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p5_.onnx) | 271MB | -| 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P6](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6.onnx) | 487MB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P6+BoF](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p6_.onnx) | 487MB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | +| [ScaledYOLOv4-P7](https://bj.bcebos.com/paddlehub/fastdeploy/scaled_yolov4-p7.onnx) | 1.1GB | - | 此模型文件来源于[ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)，GPL-3.0 License | ## 详细部署文档 diff --git a/examples/vision/detection/yolor/README.md b/examples/vision/detection/yolor/README.md index ffe29f39f..c9749a088 100644 --- a/examples/vision/detection/yolor/README.md +++ b/examples/vision/detection/yolor/README.md @@ -22,19 +22,18 @@ ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了YOLOR导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [YOLOR-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-1280-1280.onnx) | 143MB | 54.1% | -| [YOLOR-W6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-1280-1280.onnx) | 305MB | 55.5% | -| [YOLOR-E6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-1280-1280.onnx ) | 443MB | 56.4% | -| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-1280-1280.onnx) | 580MB | 57.0% | -| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-1280-1280.onnx) | 580MB | 57.3% | -| [YOLOR-P6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-640-640.onnx) | 143MB | - | -| [YOLOR-W6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-640-640.onnx) | 305MB | - | -| [YOLOR-E6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-640-640.onnx ) | 443MB | - | -| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-640-640.onnx) | 580MB | - | -| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-640-640.onnx) | 580MB | - | - +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- |:----- | +| [YOLOR-P6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-1280-1280.onnx) | 143MB | 54.1% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-W6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-1280-1280.onnx) | 305MB | 55.5% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-E6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-1280-1280.onnx ) | 443MB | 56.4% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-1280-1280.onnx) | 580MB | 57.0% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-D6-1280](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-1280-1280.onnx) | 580MB | 57.3% | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-P6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-p6-paper-541-640-640.onnx) | 143MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-W6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-w6-paper-555-640-640.onnx) | 305MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-E6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-e6-paper-564-640-640.onnx ) | 443MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-570-640-640.onnx) | 580MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | +| [YOLOR-D6](https://bj.bcebos.com/paddlehub/fastdeploy/yolor-d6-paper-573-640-640.onnx) | 580MB | - | 此模型文件来源于[YOLOR](https://github.com/WongKinYiu/yolor)，GPL-3.0 License | ## 详细部署文档 diff --git a/examples/vision/detection/yolov5/README.md b/examples/vision/detection/yolov5/README.md index 095c8071d..5ffe3f046 100644 --- a/examples/vision/detection/yolov5/README.md +++ b/examples/vision/detection/yolov5/README.md @@ -8,13 +8,13 @@ ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了YOLOv5导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [YOLOv5n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5n.onnx) | 7.6MB | 28.0% | -| [YOLOv5s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5s.onnx) | 28MB | 37.4% | -| [YOLOv5m](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5m.onnx) | 82MB | 45.4% | -| [YOLOv5l](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5l.onnx) | 178MB | 49.0% | -| [YOLOv5x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5x.onnx) | 332MB | 50.7% | +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- |:---- | +| [YOLOv5n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5n.onnx) | 7.6MB | 28.0% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License | +| [YOLOv5s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5s.onnx) | 28MB | 37.4% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License | +| [YOLOv5m](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5m.onnx) | 82MB | 45.4% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License | +| [YOLOv5l](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5l.onnx) | 178MB | 49.0% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License | +| [YOLOv5x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov5x.onnx) | 332MB | 50.7% | 此模型文件来源于[YOLOv5](https://github.com/ultralytics/yolov5)，GPL-3.0 License | ## 详细部署文档 diff --git a/examples/vision/detection/yolov5lite/README.md b/examples/vision/detection/yolov5lite/README.md index e8f72099b..0429758b8 100644 --- a/examples/vision/detection/yolov5lite/README.md +++ b/examples/vision/detection/yolov5lite/README.md @@ -52,12 +52,12 @@ ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了YOLOv5Lite导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [YOLOv5Lite-e](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-e-sim-320.onnx) | 3.1MB | 35.1% | -| [YOLOv5Lite-s](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-s-sim-416.onnx) | 6.3MB | 42.0% | -| [YOLOv5Lite-c](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-c-sim-512.onnx) | 18MB | 50.9% | -| [YOLOv5Lite-g](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-g-sim-640.onnx) | 21MB | 57.6% | +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- |:----- | +| [YOLOv5Lite-e](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-e-sim-320.onnx) | 3.1MB | 35.1% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License ｜ +| [YOLOv5Lite-s](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-s-sim-416.onnx) | 6.3MB | 42.0% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License | +| [YOLOv5Lite-c](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-c-sim-512.onnx) | 18MB | 50.9% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License | +| [YOLOv5Lite-g](https://bj.bcebos.com/paddlehub/fastdeploy/v5Lite-g-sim-640.onnx) | 21MB | 57.6% | 此模型文件来源于[YOLOv5-Lite](https://github.com/ppogg/YOLOv5-Lite)，GPL-3.0 License | ## 详细部署文档 diff --git a/examples/vision/detection/yolov6/README.md b/examples/vision/detection/yolov6/README.md index 6c0ca0422..d31622a8b 100644 --- a/examples/vision/detection/yolov6/README.md +++ b/examples/vision/detection/yolov6/README.md @@ -11,13 +11,12 @@ ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了YOLOv6导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [YOLOv6s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s.onnx) | 66MB | 43.1% | -| [YOLOv6s_640](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s-640x640.onnx) | 66MB | 43.1% | -| [YOLOv6t](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6t.onnx) | 58MB | 41.3% | -| [YOLOv6n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6n.onnx) | 17MB | 35.0% | - +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- |:----- | +| [YOLOv6s](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s.onnx) | 66MB | 43.1% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License | +| [YOLOv6s_640](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s-640x640.onnx) | 66MB | 43.1% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License | +| [YOLOv6t](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6t.onnx) | 58MB | 41.3% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License | +| [YOLOv6n](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6n.onnx) | 17MB | 35.0% | 此模型文件来源于[YOLOv6](https://github.com/meituan/YOLOv6)，GPL-3.0 License | ## 详细部署文档 diff --git a/examples/vision/detection/yolov7/README.md b/examples/vision/detection/yolov7/README.md index 925c26100..d07350fbc 100644 --- a/examples/vision/detection/yolov7/README.md +++ b/examples/vision/detection/yolov7/README.md @@ -27,16 +27,14 @@ python models/export.py --grid --dynamic --end2end --weights PATH/TO/yolov7.pt ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了YOLOv7导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% | -| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% | -| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% | -| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% | -| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% | -| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% | - - +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- | :----- | +| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | ## 详细部署文档 diff --git a/examples/vision/detection/yolov7/README_EN.md b/examples/vision/detection/yolov7/README_EN.md index 83394f52c..04001beb7 100644 --- a/examples/vision/detection/yolov7/README_EN.md +++ b/examples/vision/detection/yolov7/README_EN.md @@ -24,14 +24,14 @@ python models/export.py --grid --dynamic --end2end --weights PATH/TO/yolov7.pt To facilitate testing for developers, we provide below the models exported by YOLOv7, which developers can download and use directly. (The accuracy of the models in the table is sourced from the official library) -| Model | Size | Accuracy | -| ------------------------------------------------------------------------ | ----- | -------- | -| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% | -| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% | -| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% | -| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% | -| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% | -| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% | +| Model | Size | Accuracy | Note | +| ------------------------------------------------------------------------ | ----- | -------- | -------- | +| [YOLOv7](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7.onnx) | 141MB | 51.4% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License | +| [YOLOv7x](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x.onnx) | 273MB | 53.1% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License | +| [YOLOv7-w6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6.onnx) | 269MB | 54.9% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License | +| [YOLOv7-e6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6.onnx) | 372MB | 56.0% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License | +| [YOLOv7-d6](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6.onnx) | 511MB | 56.6% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License | +| [YOLOv7-e6e](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e.onnx) | 579MB | 56.8% | This model file comes from [YOLOv7](https://github.com/WongKinYiu/yolov7), GPL-3.0 License | ## Detailed Deployment Tutorials diff --git a/examples/vision/detection/yolov7end2end_ort/README.md b/examples/vision/detection/yolov7end2end_ort/README.md index fdfd08019..8b733bd25 100644 --- a/examples/vision/detection/yolov7end2end_ort/README.md +++ b/examples/vision/detection/yolov7end2end_ort/README.md @@ -20,14 +20,14 @@ python export.py --weights yolov7.pt --grid --end2end --simplify --topk-all 100 ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了YOLOv7End2EndORT导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [yolov7-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-end2end-ort-nms.onnx) | 141MB | 51.4% | -| [yolov7x-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x-end2end-ort-nms.onnx) | 273MB | 53.1% | -| [yolov7-w6-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6-end2end-ort-nms.onnx) | 269MB | 54.9% | -| [yolov7-e6-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6-end2end-ort-nms.onnx) | 372MB | 56.0% | -| [yolov7-d6-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6-end2end-ort-nms.onnx) | 511MB | 56.6% | -| [yolov7-e6e-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e-end2end-ort-nms.onnx) | 579MB | 56.8% | +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- |:----- | +| [yolov7-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-end2end-ort-nms.onnx) | 141MB | 51.4% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7x-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x-end2end-ort-nms.onnx) | 273MB | 53.1% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-w6-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6-end2end-ort-nms.onnx) | 269MB | 54.9% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-e6-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6-end2end-ort-nms.onnx) | 372MB | 56.0% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-d6-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6-end2end-ort-nms.onnx) | 511MB | 56.6% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-e6e-end2end-ort-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e-end2end-ort-nms.onnx) | 579MB | 56.8% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | ## 详细部署文档 diff --git a/examples/vision/detection/yolov7end2end_trt/README.md b/examples/vision/detection/yolov7end2end_trt/README.md index 9e6d30cdf..04be6f568 100644 --- a/examples/vision/detection/yolov7end2end_trt/README.md +++ b/examples/vision/detection/yolov7end2end_trt/README.md @@ -22,14 +22,14 @@ python export.py --weights yolov7.pt --grid --end2end --simplify --topk-all 100 ## 下载预训练ONNX模型 为了方便开发者的测试，下面提供了YOLOv7End2EndTRT 导出的各系列模型，开发者可直接下载使用。（下表中模型的精度来源于源官方库） -| 模型 | 大小 | 精度 | -|:---------------------------------------------------------------- |:----- |:----- | -| [yolov7-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-end2end-trt-nms.onnx) | 141MB | 51.4% | -| [yolov7x-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x-end2end-trt-nms.onnx) | 273MB | 53.1% | -| [yolov7-w6-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6-end2end-trt-nms.onnx) | 269MB | 54.9% | -| [yolov7-e6-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6-end2end-trt-nms.onnx) | 372MB | 56.0% | -| [yolov7-d6-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6-end2end-trt-nms.onnx) | 511MB | 56.6% | -| [yolov7-e6e-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e-end2end-trt-nms.onnx) | 579MB | 56.8% | +| 模型 | 大小 | 精度 | 备注 | +|:---------------------------------------------------------------- |:----- |:----- |:----- | +| [yolov7-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-end2end-trt-nms.onnx) | 141MB | 51.4% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7x-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7x-end2end-trt-nms.onnx) | 273MB | 53.1% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-w6-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-w6-end2end-trt-nms.onnx) | 269MB | 54.9% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-e6-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6-end2end-trt-nms.onnx) | 372MB | 56.0% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-d6-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-d6-end2end-trt-nms.onnx) | 511MB | 56.6% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | +| [yolov7-e6e-end2end-trt-nms](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-e6e-end2end-trt-nms.onnx) | 579MB | 56.8% | 此模型文件来源于[YOLOv7](https://github.com/WongKinYiu/yolov7)，GPL-3.0 License | ## 详细部署文档 From edc18c9fc81bc6f3b0ac60df4daecda0080ee31d Mon Sep 17 00:00:00 2001 From: Zeref996 <53218160+Zeref996@users.noreply.github.com> Date: Thu, 5 Jan 2023 13:39:40 +0800 Subject: [PATCH 6/6] fix serving/Dockerfile http_proxy (#1066) fix serving/Dockerfile --- serving/Dockerfile | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/serving/Dockerfile b/serving/Dockerfile index e0079694a..70a595cae 100644 --- a/serving/Dockerfile +++ b/serving/Dockerfile @@ -41,8 +41,12 @@ RUN apt-get update \ RUN apt-get update \ && apt-get install -y --no-install-recommends libre2-5 libb64-0d python3 python3-pip libarchive-dev ffmpeg libsm6 libxext6 \ && python3 -m pip install -U pip \ - && python3 -m pip install paddlenlp fast-tokenizer-python \ - && python3 -m pip install paddlepaddle-gpu==2.4.1.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html + && python3 -m pip install paddlenlp fast-tokenizer-python + +# unset proxy +ENV http_proxy= +ENV https_proxy= +python3 -m pip install paddlepaddle-gpu==2.4.1.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html COPY python/dist/*.whl /opt/fastdeploy/ RUN python3 -m pip install /opt/fastdeploy/*.whl \ @@ -53,6 +57,3 @@ COPY build/fastdeploy_install /opt/fastdeploy/ ENV LD_LIBRARY_PATH="/opt/TensorRT-8.4.1.5/lib/:/opt/fastdeploy/lib:/opt/fastdeploy/third_libs/install/onnxruntime/lib:/opt/fastdeploy/third_libs/install/paddle2onnx/lib:/opt/fastdeploy/third_libs/install/tensorrt/lib:/opt/fastdeploy/third_libs/install/paddle_inference/paddle/lib:/opt/fastdeploy/third_libs/install/paddle_inference/third_party/install/mkldnn/lib:/opt/fastdeploy/third_libs/install/paddle_inference/third_party/install/mklml/lib:/opt/fastdeploy/third_libs/install/openvino/runtime/lib:$LD_LIBRARY_PATH" ENV PATH="/opt/tritonserver/bin:$PATH" -# unset proxy -ENV http_proxy= -ENV https_proxy=