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⚡️फास्टडिप्लोयएक एआई अनुमान तैनाती उपकरण है जो सभी परिदृश्य, उपयोग करने में आसान और लचीला और बेहद कुशल है। एक📦आउट-ऑफ-द-बॉक्स क्लाउड-एज परिनियोजन अनुभव प्रदान करता है, 🔥160+ से अधिक टेक्स्ट, विजन, स्पीच और क्रॉस-मोडल मॉडल का समर्थन करता है, और 🔚 एंड-टू-एंड अनुमान प्रदर्शन अनुकूलन को लागू करता है। डेवलपर्स की जरूरतों को पूरा करने के लिए छवि वर्गीकरण, ऑब्जेक्ट डिटेक्शन, छवि विभाजन, चेहरे का पता लगाने, चेहरे की पहचान, मुख्य बिंदु का पता लगाने, कटआउट, ओसीआर, एनएलपी, टीटीएस और अन्य कार्यों सहित बहु-परिदृश्य, बहु-हार्डवेयर, बहु-मंच उद्योग की तैनाती की जरूरत है।
✨✨✨ 2023.01.17 यह रिलीज फास्ट डिसेनियोजित हार्डवेयर श्रृंखला पर YOLOv8 की तैनाती का समर्थन करता है। जो भी शामिल Paddle YOLOv8 तथा समुदाय ultralytics YOLOv8
✨👥✨ सामुदायिक संचार
Slack:Join our Slack community and chat with other community members about ideas
WeChat: दो आयामी कोड स्कैन करें, तकनीकी समुदाय में शामिल होने के लिए प्रश्नावली भरें और समुदाय डेवलपर्स के साथ तैनात उद्योग से होने वाले दर्द बिंदुओं के बारे में संवाद करें।
वीडियो स्ट्रीम | सेवाकरण परिनियोजन | एंड टू एंड परफॉरमेंस ऑप्टिमाइज़ेशन। | Linux | Windows | Android | macOS | |
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NVDIA GPU |
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Phytium CPU |
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KunlunXin XPU | |||||||
Huawei Ascend NPU |
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Graphcore IPU | |||||||
Sophgo | |||||||
Intel graphics card | |||||||
Jetson |
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ARM CPU |
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NXP |
pip install numpy opencv-python fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2
pip install numpy opencv-python fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
tar xvf ppyoloe_crn_l_300e_coco.tgz
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
# GPU/TensorRT तैनाती, संदर्भ examples/vision/detection/paddledetection/python
import cv2
import fastdeploy.vision as vision
model = vision.detection.PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
"ppyoloe_crn_l_300e_coco/model.pdiparams",
"ppyoloe_crn_l_300e_coco/infer_cfg.yml")
im = cv2.imread("000000014439.jpg")
result = model.predict(im)
print(result)
vis_im = vision.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("vis_image.jpg", vis_im)
wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
tar xvf ppyoloe_crn_l_300e_coco.tgz
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
// GPU/TensorRT तैनाती, संदर्भ examples/vision/detection/paddledetection/cpp
#include "fastdeploy/vision.h"
int main(int argc, char* argv[]) {
namespace vision = fastdeploy::vision;
auto model = vision::detection::PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
"ppyoloe_crn_l_300e_coco/model.pdiparams",
"ppyoloe_crn_l_300e_coco/infer_cfg.yml");
auto im = cv::imread("000000014439.jpg");
vision::DetectionResult res;
model.Predict(im, &res);
auto vis_im = vision::VisDetection(im, res, 0.5);
cv::imwrite("vis_image.jpg", vis_im);
return 0;
}
अधिक तैनाती के मामलों के लिए, देखेंमॉडल परिनियोजन उदाहरण .
प्रतीक विवरण: (1) ✅: पहले से समर्थित; (2) ❔:गति पर ; (3) N/A: समर्थित नहीं;
कार्य परिदृश्य | नमूना | Linux | Linux | Win | Win | Mac | Mac | Linux | Linux | Linux | Linux | Linux |
---|---|---|---|---|---|---|---|---|---|---|---|---|
--- | --- | X86 CPU | NVIDIA GPU | X86 CPU | NVIDIA GPU | X86 CPU | Arm CPU | AArch64 CPU | Phytium D2000CPU | NVIDIA Jetson | Graphcore IPU | Serving |
Classification | PaddleClas/ResNet50 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | TorchVison/ResNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Classification | ultralytics/YOLOv5Cls | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Classification | PaddleClas/PP-LCNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/PP-LCNetv2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/EfficientNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/GhostNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/MobileNetV1 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/MobileNetV2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/MobileNetV3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/ShuffleNetV2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/SqueeezeNetV1.1 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Classification | PaddleClas/Inceptionv3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Classification | PaddleClas/PP-HGNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
Detection | PaddleDetection/PP-YOLOE | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | 🔥PaddleDetection/YOLOv8 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | 🔥ultralytics/YOLOv8 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Detection | PaddleDetection/PicoDet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | PaddleDetection/YOLOX | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | PaddleDetection/YOLOv3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | PaddleDetection/PP-YOLO | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | PaddleDetection/PP-YOLOv2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | PaddleDetection/Faster-RCNN | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | PaddleDetection/Mask-RCNN | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | Megvii-BaseDetection/YOLOX | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Detection | WongKinYiu/YOLOv7 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Detection | WongKinYiu/YOLOv7end2end_trt | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Detection | WongKinYiu/YOLOv7end2end_ort_ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Detection | meituan/YOLOv6 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Detection | ultralytics/YOLOv5 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Detection | WongKinYiu/YOLOR | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Detection | WongKinYiu/ScaledYOLOv4 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Detection | ppogg/YOLOv5Lite | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Detection | RangiLyu/NanoDetPlus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
KeyPoint | PaddleDetection/TinyPose | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
KeyPoint | PaddleDetection/PicoDet + TinyPose | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
HeadPose | omasaht/headpose | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Tracking | PaddleDetection/PP-Tracking | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
OCR | PaddleOCR/PP-OCRv2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
OCR | PaddleOCR/PP-OCRv3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ |
Segmentation | PaddleSeg/PP-LiteSeg | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Segmentation | PaddleSeg/PP-HumanSegLite | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Segmentation | PaddleSeg/HRNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Segmentation | PaddleSeg/PP-HumanSegServer | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Segmentation | PaddleSeg/Unet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Segmentation | PaddleSeg/Deeplabv3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
FaceDetection | biubug6/RetinaFace | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceDetection | Linzaer/UltraFace | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceDetection | deepcam-cn/YOLOv5Face | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceDetection | insightface/SCRFD | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceAlign | Hsintao/PFLD | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceAlign | Single430FaceLandmark1000 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
FaceAlign | jhb86253817/PIPNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
FaceRecognition | insightface/ArcFace | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceRecognition | insightface/CosFace | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceRecognition | insightface/PartialFC | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
FaceRecognition | insightface/VPL | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Matting | ZHKKKe/MODNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Matting | PeterL1n/RobustVideoMatting | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Matting | PaddleSeg/PP-Matting | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Matting | PaddleSeg/PP-HumanMatting | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Matting | PaddleSeg/ModNet | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ |
Video Super-Resolution | PaddleGAN/BasicVSR | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Video Super-Resolution | PaddleGAN/EDVR | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Video Super-Resolution | PaddleGAN/PP-MSVSR | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ |
Information Extraction | PaddleNLP/UIE | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ✅ | ❔ | |
NLP | PaddleNLP/ERNIE-3.0 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | ❔ | ✅ |
Speech | PaddleSpeech/PP-TTS | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❔ | ❔ | -- | ✅ |
कार्य परिदृश्य | नमूना | आकार(MB) | Linux | Android | Linux | Linux | Linux | Linux | Linux | TBD... |
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--- | --- | --- | ARM CPU | ARM CPU | Rockchip-NPU RK3568/RK3588 |
Rockchip-NPU RV1109/RV1126/RK1808 |
Amlogic-NPU A311D/S905D/C308X |
NXP-NPU i.MX 8M Plus |
TBD...| | |
Classification | PaddleClas/ResNet50 | 98 | ✅ | ✅ | ❔ | ✅ | ||||
Classification | PaddleClas/PP-LCNet | 11.9 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/PP-LCNetv2 | 26.6 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/EfficientNet | 31.4 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/GhostNet | 20.8 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/MobileNetV1 | 17 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/MobileNetV2 | 14.2 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/MobileNetV3 | 22 | ✅ | ✅ | ❔ | ✅ | ❔ | ❔ | -- | |
Classification | PaddleClas/ShuffleNetV2 | 9.2 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/SqueezeNetV1.1 | 5 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/Inceptionv3 | 95.5 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Classification | PaddleClas/PP-HGNet | 59 | ✅ | ✅ | ❔ | ✅ | -- | -- | -- | |
Detection | PaddleDetection/PicoDet_s | 4.9 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | -- | |
Detection | YOLOv5 | ❔ | ❔ | ✅ | ❔ | ❔ | ❔ | -- | ||
Face Detection | deepinsight/SCRFD | 2.5 | ✅ | ✅ | ✅ | -- | -- | -- | -- | |
Keypoint Detection | PaddleDetection/PP-TinyPose | 5.5 | ✅ | ✅ | ❔ | ❔ | ❔ | ❔ | -- | |
Segmentation | PaddleSeg/PP-LiteSeg(STDC1) | 32.2 | ✅ | ✅ | ✅ | -- | -- | -- | -- | |
Segmentation | PaddleSeg/PP-HumanSeg-Lite | 0.556 | ✅ | ✅ | ✅ | -- | -- | -- | -- | |
Segmentation | PaddleSeg/HRNet-w18 | 38.7 | ✅ | ✅ | ✅ | -- | -- | -- | -- | |
Segmentation | PaddleSeg/PP-HumanSeg | 107.2 | ✅ | ✅ | ✅ | -- | -- | -- | -- | |
Segmentation | PaddleSeg/Unet | 53.7 | ✅ | ✅ | ✅ | -- | -- | -- | -- | |
Segmentation | PaddleSeg/Deeplabv3 | 150 | ❔ | ✅ | ✅ | |||||
OCR | PaddleOCR/PP-OCRv2 | 2.3+4.4 | ✅ | ✅ | ❔ | -- | -- | -- | -- | |
OCR | PaddleOCR/PP-OCRv3 | 2.4+10.6 | ✅ | ❔ | ❔ | ❔ | ❔ | ❔ | -- |
कार्य परिदृश्य | नमूना | web_demo |
---|---|---|
--- | --- | Paddle.js |
Detection | FaceDetection | ✅ |
Detection | ScrewDetection | ✅ |
Segmentation | PaddleSeg/HumanSeg | ✅ |
Object Recognition | GestureRecognition | ✅ |
Object Recognition | ItemIdentification | ✅ |
OCR | PaddleOCR/PP-OCRv3 | ✅ |
यह परियोजना SDK पीढ़ी और डाउनलोड हम EasyEdge में मुक्त और खुली क्षमताओं का उपयोग करने के लिए आभारी हैं।
FastDeploy निम्नानुसार है Apache-2.0 खुला स्रोत लाइसेंस
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