Witryna本项目先后使用了三个模型来比较板球比赛语义分割的效果,分别是U-Net、PP-LiteSeg和SegFormer。在实际检测中,PP-LiteSeg模型的预测效果还是不错的。 AI Studio DevPress官方社区 Witryna28 lis 2024 · import cv2 import numpy as np import fastdeploy as fd from PIL import Image from collections import Counter def FastdeployOption(device=0): option = fd.RuntimeOption() if device == 0: option.use_gpu() else: # 使用OpenVino推理 option.use_openvino_backend() option.use_cpu() return option 复制
FastDeploy: ⚡️An Easy-to-use and Fast Deep Learning Model …
WitrynaFastDeploy三大特点: 作为全场景高性能部署工具,FastDeploy致力于打造三个特点,与上述提及的三个痛点相对应,分别是全场景、简单易用和极致高效。 01 全场景. 全场景是指FastDeploy的多端多引擎加速部署、多框架模型支持和多硬件部署能力。 多端部署 Witryna⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models. how many pending offers fall through
FastDeploy/pptinypose_infer.py at develop - Github
Witryna6 mar 2024 · 再补充一个发现,import paddle 和 import fastdeploy 的顺序不同,报的错误也不同:. (1)先 paddle ,后 fastdeploy: import import fastdeploy as fd. During handling of the above exception, another exception occurred: init. import fastdeploy as import paddle. init. init. init. Witryna13 lis 2024 · Documentation. ⚡️ FastDeploy is an Easy-to-use and High Performance AI model deployment toolkit for Cloud, Mobile and Edge with 📦 out-of-the-box and unified experience, 🔚 end-to-end optimization for over 🔥 150+ Text, Vision, Speech and Cross-modal AI models . Including image classification, object detection, image … Witryna12 paź 2024 · import cv2 import numpy as np import fastdeploy as fd from PIL import Image from collections import Counter def FastdeployOption(device=0): option = fd.RuntimeOption() if device == 0: option.use_gpu() else: # 使用OpenVino推理 option.use_openvino_backend() option.use_cpu() return option ... how can chromosomes be identified