Reproduction process of AlexNet

Last update: Nov 29, 2022

Related tags

Deep Learning AlexNet-Prod

Overview

PaddlePaddle论文复现杂谈

背景

注：该repo基于PaddlePaddle，对AlexNet进行复现。时间仓促，难免有所疏漏，如果问题或者想法，欢迎随时提issue一块交流。

飞桨论文复现赛地址：https://aistudio.baidu.com/aistudio/competition/detail/106

不可多得的学习过程中还能搞钱的机会，欢迎大家积极报名。

介绍

目录结构

AlexNet-torch: 将pytorch代码中与AlexNet图像分类任务有关的代码抽取出来，用于复现
AlexNet-paddle：基于AlexNet-torch进行的AlexNet模型复现。
notebook：整理PPT过程中遇到过的一些代码小片段，算是一点小随笔了。

注意：这里为了严格保持对齐的步骤，将数据集中的每个类别对应的图片都装在了同一个文件夹中，但是实际上，使用train_list.txt这种文本的方式去记录训练数据列表，整体训练文件会更加灵活可控一些，更加具体的实现可以参考：PaddleClas中的数据读取部分。

官方模型套件指路。

图像分类和识别PaddleClas： https://github.com/PaddlePaddle/PaddleClas
文字检测和识别PaddleOCR： https://github.com/PaddlePaddle/PaddleOCR
目标检测PaddleDetection： https://github.com/PaddlePaddle/PaddleDetection
图像分割PaddleSeg： https://github.com/PaddlePaddle/PaddleSeg
生成对抗网络PaddleGAN： https://github.com/PaddlePaddle/PaddleGAN
视频分类PaddleVideo： https://github.com/PaddlePaddle/PaddleVideo
文本理解PaddleNLP： https://github.com/PaddlePaddle/PaddleNLP

欢迎贡献

如果您有更多有意思的paddle代码小片段，也欢迎提个pr，上传到notebook文件夹，可以是一些自己实现的骚操作，也可以是一些组合的一些api，也可以是自己在使用过程中觉得有意思的功能。
如果您有更多已经复现的文章或者方法，如果有兴趣提交的话，可以新建一个文件夹，命名为xxxx-paddle，其中xxxx表示复现的算法或者名称，将自己的代码放在该文件夹下，然后提交PR即可。
生命不息，开源不止，感谢您的使用和关注，希望我们可以一起用飞桨划出一个更有意思的时代。

Code for Transformer Hawkes Process, ICML 2020.

Transformer Hawkes Process Source code for Transformer Hawkes Process (ICML 2020). Run the code Dependencies Python 3.7. Anaconda contains all the req

111 Dec 26, 2022

Multi-Output Gaussian Process Toolkit

Multi-Output Gaussian Process Toolkit Paper - API Documentation - Tutorials & Examples The Multi-Output Gaussian Process Toolkit is a Python toolkit f

113 Nov 25, 2022

Official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch.

Multi-speaker DGP This repository provides official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch. O

24 Sep 7, 2022

Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"

Code To run: python runner.py new --save SAVE_NAME --data PATH_TO_DATA_DIR --dataset DATASET --model model_name [options] --n 1000 - train - t

5 Dec 12, 2022

Convenient tool for speeding up the intern/officer review process.

icpc-app-screen Convenient tool for speeding up the intern/officer applicant review process. Eliminates the pain from reading application responses of

1 Oct 30, 2021

Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport

Non-Homogeneous Poisson Process Intensity Modeling and Estimation using Measure Transport This GitHub page provides code for reproducing the results i

1 Nov 8, 2021

A Python package to process & model ChEMBL data.

insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper

0 Dec 9, 2021

A set of simple scripts to process the Imagenet-1K dataset as TFRecords and make index files for NVIDIA DALI.

Overview This is a set of simple scripts to process the Imagenet-1K dataset as TFRecords and make index files for NVIDIA DALI. Make TFRecords To run t

8 Nov 1, 2022

This is a GUI interface which can process forest fire detection, smoke detection and fire segmentation

This is a GUI interface which can process forest fire detection, smoke detection and fire segmentation. Yolov5 is used to detect fire and smoke and unet is used to segment fire.

7 Jan 8, 2023

Comments

torch2paddle.py提示错误

torch2paddle.py中

def transfer():
    input_fp = "resnet50-0676ba61.pth"
    output_fp = "model.pdparams"
    # torch_dict = torch.load(input_fp)['model']

提示

Traceback (most recent call last):
  File "H:/论文复现0814/ResNet50-livingbody/torch2paddle.py", line 71, in <module>
    transfer()
  File "H:/论文复现0814/ResNet50-livingbody/torch2paddle.py", line 31, in transfer
    torch_dict = torch.load(input_fp)['model']
KeyError: 'model'

opened by livingbody 0

关于服务端部署预测

我在使用您给的服务端部署示例中，已经走通了全部流程，可是只能输出一个结果输出如下： {'err_no': 0, 'err_msg': '', 'key': ['class_id', 'confidence', 'left_top', 'right_bottom'], 'value': ['[0]', '[0.92535084]', '[[283.15506, 8.095686]]', '[[636.6692, 391.48724]]'], 'tensors': []} 我做的任务是目标检测，在 infer 中，输出有 4 个 boxes，这里只显示了第一个，我换了一张图也是一样，只会输出第一个 boxes 的结果，输出的这个结果是完全和 infer 对的上的，只是还有几个没有输出。于是，我打印了 fetch_dict 结果如下： {'concat_5.tmp_0': array([100], dtype=int32), 'concat_6.tmp_0': array([[ 0. , 0.92535084, 283.15506 , 8.095686 , 636.6692 , 391.48724 ]], dtype=float32)} “concat_5.tmp_0” 中的 100 表示预测的结果有 100 个 boxes，“concat_6.tmp_0” 按理说应该有 100 个结果。

opened by FL77N 1

Owner

https://blog.csdn.net/u012526003

GitHub

A PyTorch Image-Classification With AlexNet And ResNet50.

PyTorch 图像分类依赖库的下载与安装在终端中执行 pip install -r -requirements.txt 完成项目依赖库的安装使用方式数据集的准备 STL10 数据集下载：STL-10 Dataset 存储位置：将下载后的数据集中 train_X.bin,train_y.b

4 Feb 22, 2022

NFT-Price-Prediction-CNN - Using visual feature extraction, prices of NFTs are predicted via CNN (Alexnet and Resnet) architectures.

5 Nov 3, 2022

A pytorch reproduction of { Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation }.

A PyTorch Reproduction of HCN Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation. Ch

210 Dec 31, 2022