{"id":22007376,"url":"https://github.com/elite-sheep/vgg16","last_synced_at":"2026-05-02T01:31:30.487Z","repository":{"id":112599484,"uuid":"128033680","full_name":"elite-sheep/vgg16","owner":"elite-sheep","description":"A vgg16 implementation with tensorflow-python","archived":false,"fork":false,"pushed_at":"2018-04-20T08:09:23.000Z","size":14,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-23T07:14:41.640Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/elite-sheep.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-04-04T08:42:13.000Z","updated_at":"2018-04-20T08:09:20.000Z","dependencies_parsed_at":null,"dependency_job_id":"bd2f3fed-f61a-4de0-b3bf-80f214a9a6a4","html_url":"https://github.com/elite-sheep/vgg16","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/elite-sheep/vgg16","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elite-sheep%2Fvgg16","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elite-sheep%2Fvgg16/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elite-sheep%2Fvgg16/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elite-sheep%2Fvgg16/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/elite-sheep","download_url":"https://codeload.github.com/elite-sheep/vgg16/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/elite-sheep%2Fvgg16/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32520156,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-02T01:12:54.858Z","status":"ssl_error","status_checked_at":"2026-05-02T01:12:54.261Z","response_time":64,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-30T01:25:38.840Z","updated_at":"2026-05-02T01:31:30.461Z","avatar_url":"https://github.com/elite-sheep.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# VGG16\n\nThis a implementation of vgg16 with tensorflow and python, study-oriented.\n\n## Overview of vgg16\n\n**vgg16** is an important convolutional neural network posted by Karen Simonyan. The link of their essay is here below:  \n**https://arxiv.org/abs/1409.1556**  \n\n## Usage\n\n### Train\n\nTo train vgg16 with this project, you only need to provide a path. The path should contain a file named \"model.json\" and this JSON\nfile contains all information to train a vgg16 network with this project.  \n\nA sample **model.json** is shown below:  \n\n```\n{\n\t\"learning_rate\":0.01,\n\t\"momentum\":0.9,\n\t\"batchsize\":8,\n\t\"batches\":70,\n\t\"channel\":3,\n\t\"classes\":2,\n\t\"classnamelist\":\"labels.txt\",\n\t\"trainlist\":\"train.txt\",\n\t\"labellist\":\"labellist.txt\"\n}\n```\n\nThe **classnamelist** is a file that contains all names of classes. The number of classes should be equal to the number of classes that\nprovides in \"model.json\".  \n\nThe **trainlist** file contains the absolute path to all pictures in the training set.  \nThe **labellist** file contains the index of class of a picture, corresponding to the index of pictures in the **trainlist**.  \n\nTo train a vgg16 using this project:  \n\n```python\n#!coding=utf-8\n\nfrom src.vgg16 import Vgg16\n\ndef main():\n\t\t#init a new Vgg16 instance\n    net = Vgg16()\n\t\t#load json file\n    net.loadWithUntrainedJson(srcDir=\"./example\")\n\t\t#train CNN, the model will be deployed in tgtDir\n    net.train(tgtDir='./example')\n\nif __name__ == '__main__':\n    main()\n```\n\n### Predict\n\nWe provide a predict API to predict from a image list. The API is shown below:  \n\n```python\ndef predict(self, tgtDir, imageListFile)\n```\n\nBefore you use the model to predict, the model should be loaded with the following API:  \n\n```python\ndef loadWithTrainedJson(self, modelDir)\n```\n\nThe **modelDir** contains the model trained with this project or created \nby the users themselves.  \n\nThe **imageListFile** is the list of images to be predicted. Each line of the file contains an \naddress of an image(we encourage absolute address).  \n\nAt last, the result will dump to **result.txt** to **tgtDir**.  \n\n### More\n\nFurther question, please contact **wyc8094@gmail.com**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felite-sheep%2Fvgg16","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Felite-sheep%2Fvgg16","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felite-sheep%2Fvgg16/lists"}