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[YOLOv8] Add PaddleYOLOv8 models download links #1152

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merged 17 commits into from
Jan 16, 2023
Merged

[YOLOv8] Add PaddleYOLOv8 models download links #1152

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d2a0a7c
[Model] Support PaddleYOLOv8 model
DefTruth Jan 13, 2023
2bfbeb9
[YOLOv8] Add PaddleYOLOv8 pybind
DefTruth Jan 14, 2023
c47a2fa
[Other] update from latest develop (#30)
DefTruth Jan 14, 2023
2c00512
Merge branch 'support_paddle_yolov8' of https://github.com/DefTruth/F…
DefTruth Jan 14, 2023
e0072cc
Merge branch 'develop' into support_paddle_yolov8
DefTruth Jan 14, 2023
a031d9f
[YOLOv8] add PaddleYOLOv8 pybind11 (#1144) (#31)
DefTruth Jan 14, 2023
d3b4f5e
[benchmark] add PaddleYOLOv8 -> benchmark
DefTruth Jan 14, 2023
9e7ec4f
[benchmark] add PaddleYOLOv8 -> benchmark
DefTruth Jan 14, 2023
d933b23
[Lite] Support PaddleYOLOv8 with Lite Backend
DefTruth Jan 14, 2023
21d66b6
Merge branch 'develop' into support_paddle_yolov8
DefTruth Jan 14, 2023
6348aa8
[Pick] Update from latest develop (#32)
DefTruth Jan 15, 2023
7d647be
[YOLOv8] Support PaddleYOLOv8 on Kunlunxin&Ascend
DefTruth Jan 15, 2023
355035e
Merge branch 'support_paddle_yolov8' of https://github.com/DefTruth/F…
DefTruth Jan 15, 2023
3bfe062
[YOLOv8] Add PaddleYOLOv8 model download links
DefTruth Jan 16, 2023
7bf07a1
Merge branch 'PaddlePaddle:develop' into support_paddle_yolov8
DefTruth Jan 16, 2023
bc3b4cd
Merge branch 'support_paddle_yolov8' of https://github.com/DefTruth/F…
DefTruth Jan 16, 2023
e5410e7
[YOLOv8] Add PaddleYOLOv8 Box AP
DefTruth Jan 16, 2023
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38 changes: 35 additions & 3 deletions benchmark/benchmark_ppdet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,17 +43,22 @@ def parse_arguments():
parser.add_argument(
"--device",
default="cpu",
help="Type of inference device, support 'cpu' or 'gpu'.")
help="Type of inference device, support 'cpu', 'gpu', 'kunlunxin', 'ascend' etc.")
parser.add_argument(
"--backend",
type=str,
default="default",
help="inference backend, default, ort, ov, trt, paddle, paddle_trt.")
help="inference backend, default, ort, ov, trt, paddle, paddle_trt, lite.")
parser.add_argument(
"--enable_trt_fp16",
type=ast.literal_eval,
default=False,
help="whether enable fp16 in trt backend")
parser.add_argument(
"--enable_lite_fp16",
type=ast.literal_eval,
default=False,
help="whether enable fp16 in lite backend")
parser.add_argument(
"--enable_collect_memory_info",
type=ast.literal_eval,
Expand All @@ -68,6 +73,7 @@ def build_option(args):
device = args.device
backend = args.backend
enable_trt_fp16 = args.enable_trt_fp16
enable_lite_fp16 = args.enable_lite_fp16
option.set_cpu_thread_num(args.cpu_num_thread)
if device == "gpu":
option.use_gpu()
Expand Down Expand Up @@ -111,9 +117,35 @@ def build_option(args):
raise Exception(
"While inference with CPU, only support default/ort/ov/paddle now, {} is not supported.".
format(backend))
elif device == "kunlunxin":
option.use_kunlunxin()
if backend == "lite":
option.use_lite_backend()
elif backend == "ort":
option.use_ort_backend()
elif backend == "paddle":
option.use_paddle_backend()
elif backend == "default":
return option
else:
raise Exception(
"While inference with CPU, only support default/ort/lite/paddle now, {} is not supported.".
format(backend))
elif device == "ascend":
option.use_ascend()
if backend == "lite":
option.use_lite_backend()
if enable_lite_fp16:
option.enable_lite_fp16()
elif backend == "default":
return option
else:
raise Exception(
"While inference with CPU, only support default/lite now, {} is not supported.".
format(backend))
else:
raise Exception(
"Only support device CPU/GPU now, {} is not supported.".format(
"Only support device CPU/GPU/Kunlunxin/Ascend now, {} is not supported.".format(
device))

return option
Expand Down
29 changes: 27 additions & 2 deletions examples/vision/detection/paddledetection/README.md
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Expand Up @@ -19,8 +19,18 @@ Now FastDeploy supports the deployment of the following models
- [SSD models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd)
- [YOLOv5 models](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5)
- [YOLOv6 models](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6)
- [YOLOv7 models](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)
- [YOLOv7 models](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)
- [YOLOv8 models](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)
- [RTMDet models](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
- [RTMDet models](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
- [CascadeRCNN models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn)
- [PSSDet models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rcnn_enhance)
- [RetinaNet models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/retinanet)
- [PPYOLOESOD models](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/smalldet)
- [FCOS models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/fcos)
- [TTFNet models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ttfnet)
- [TOOD models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/tood)
- [GFL models](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/gfl)

## Export Deployment Model

Expand Down Expand Up @@ -58,7 +68,22 @@ The accuracy metric is from model descriptions in PaddleDetection. Refer to them
| [yolov6_l_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6_l_300e_coco.tgz) | 229M | Box AP 51.0%| |
| [yolov6_s_400e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov6_s_400e_coco.tgz) | 68M | Box AP 43.4%| |
| [yolov7_l_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_l_300e_coco.tgz) | 145M | Box AP 51.0%| |
| [yolov7_x_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_x_300e_coco.tgz) | 277M | Box AP 53.0%| |
| [yolov7_x_300e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_x_300e_coco.tgz) | 277M | Box AP 53.0%| |
| [cascade_rcnn_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/cascade_rcnn_r50_fpn_1x_coco.tgz) | 271M | Box AP 41.1%| TensorRT、ORT not supported yet|
| [cascade_rcnn_r50_vd_fpn_ssld_2x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/cascade_rcnn_r50_vd_fpn_ssld_2x_coco.tgz) | 271M | Box AP 45.0%| TensorRT、ORT not supported yet|
| [faster_rcnn_enhance_3x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/faster_rcnn_enhance_3x_coco.tgz) | 119M | Box AP 41.5%| TensorRT、ORT not supported yet|
| [fcos_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/fcos_r50_fpn_1x_coco.tgz) | 129M | Box AP 39.6%| TensorRT not supported yet |
| [gfl_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/gfl_r50_fpn_1x_coco.tgz) | 128M | Box AP 41.0%| TensorRT not supported yet|
| [ppyoloe_crn_l_80e_sliced_visdrone_640_025](https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_80e_sliced_visdrone_640_025.tgz) | 200M | Box AP 31.9%| |
| [retinanet_r101_fpn_2x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/retinanet_r101_fpn_2x_coco.tgz) | 210M | Box AP 40.6%| TensorRT、ORT not supported yet|
| [retinanet_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/retinanet_r50_fpn_1x_coco.tgz) | 136M | Box AP 37.5%| TensorRT、ORT not supported yet|
| [tood_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/tood_r50_fpn_1x_coco.tgz) | 130M | Box AP 42.5%| TensorRT、ORT not supported yet|
| [ttfnet_darknet53_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ttfnet_darknet53_1x_coco.tgz) | 178M | Box AP 33.5%| TensorRT、ORT not supported yet|
| [yolov8_x_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_x_500e_coco.tgz) | 265M | Box AP 53.8%
| [yolov8_l_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_l_500e_coco.tgz) | 173M | Box AP 52.8%
| [yolov8_m_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_m_500e_coco.tgz) | 99M | Box AP 50.2%
| [yolov8_s_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_s_500e_coco.tgz) | 43M | Box AP 44.9%
| [yolov8_n_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_n_500e_coco.tgz) | 13M | Box AP 37.3%

## Detailed Deployment Documents

Expand Down
10 changes: 8 additions & 2 deletions examples/vision/detection/paddledetection/README_CN.md
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,8 @@
- [SSD系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ssd)
- [YOLOv5系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5)
- [YOLOv6系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6)
- [YOLOv7系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)
- [YOLOv7系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)
- [YOLOv8系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)
- [RTMDet系列模型](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
- [CascadeRCNN系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/cascade_rcnn)
- [PSSDet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/rcnn_enhance)
Expand Down Expand Up @@ -78,7 +79,12 @@
| [retinanet_r101_fpn_2x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/retinanet_r101_fpn_2x_coco.tgz) | 210M | Box AP 40.6%| 暂不支持TensorRT、ORT |
| [retinanet_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/retinanet_r50_fpn_1x_coco.tgz) | 136M | Box AP 37.5%| 暂不支持TensorRT、ORT |
| [tood_r50_fpn_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/tood_r50_fpn_1x_coco.tgz) | 130M | Box AP 42.5%| 暂不支持TensorRT、ORT |
| [ttfnet_darknet53_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ttfnet_darknet53_1x_coco.tgz) | 178M | Box AP 33.5%| 暂不支持TensorRT、ORT |
| [ttfnet_darknet53_1x_coco](https://bj.bcebos.com/paddlehub/fastdeploy/ttfnet_darknet53_1x_coco.tgz) | 178M | Box AP 33.5%| 暂不支持TensorRT、ORT |
| [yolov8_x_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_x_500e_coco.tgz) | 265M | Box AP 53.8%
| [yolov8_l_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_l_500e_coco.tgz) | 173M | Box AP 52.8%
| [yolov8_m_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_m_500e_coco.tgz) | 99M | Box AP 50.2%
| [yolov8_s_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_s_500e_coco.tgz) | 43M | Box AP 44.9%
| [yolov8_n_500e_coco](https://bj.bcebos.com/paddlehub/fastdeploy/yolov8_n_500e_coco.tgz) | 13M | Box AP 37.3%

## 详细部署文档

Expand Down
3 changes: 3 additions & 0 deletions examples/vision/detection/paddledetection/python/infer_yolov8.py
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Expand Up @@ -32,6 +32,9 @@ def build_option(args):
if args.device.lower() == "kunlunxin":
option.use_kunlunxin()

if args.device.lower() == "ascend":
option.use_ascend()

if args.device.lower() == "gpu":
option.use_gpu()

Expand Down
1 change: 1 addition & 0 deletions fastdeploy/vision/detection/ppdet/model.h
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Expand Up @@ -256,6 +256,7 @@ class FASTDEPLOY_DECL PaddleYOLOv8 : public PPDetBase {
valid_cpu_backends = {Backend::OPENVINO, Backend::ORT, Backend::PDINFER, Backend::LITE};
valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
valid_kunlunxin_backends = {Backend::LITE};
valid_ascend_backends = {Backend::LITE};
initialized = Initialize();
}

Expand Down