{"id":23093051,"url":"https://github.com/crispengari/wac","last_synced_at":"2026-04-12T13:02:42.841Z","repository":{"id":141095442,"uuid":"576959483","full_name":"CrispenGari/WAC","owner":"CrispenGari","description":"🦁🐅WAC is an AI tool for Wild Animal Classification from a Mobile camera or Mobile Image Library. 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Given an image of the listed wild animal the model should be able to name the animal that is in that image.\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"cover.jpg\" alt=\"cover\" width=\"100%\"/\u003e\n\u003cp\u003e\n\n### WAC Tool (mobile)\n\nWAC tool is an AI tool for mobile application that is used to perform some basic wild animal image classification task in real-time. Given an image from a camera or an imported image the application must be able to classify the name or class of the wild animal on that picture in real-time.\n\n\n### API\n\nWAC api is a simple rest api that is served at `http://localhost:3001/api/v1/classify` and is able to the name of that wild animal from an image.\n\n### API response\n\nIf a proper `POST` request is sent to the server at `http://127.0.0.1:3001/api/v1/classify` we will be able to get `~93%` accurate predictions of the name of the wild animal on that image.\n\n### cURL request\n\nIf a `cURL` request is send to the server at localhost which looks as follows:\n\n```shell\ncURL -X POST -F image=@cheetah.png http://127.0.0.1:3001/api/v1/classify\n```\n\nThe server will respond with the `API` response which looks as follows:\n\n```json\n{\n  \"predictions\": {\n    \"predictions\": [\n      { \"className\": \"cheetah\", \"label\": 0, \"probability\": 0.9900000095367432 },\n      { \"className\": \"fox\", \"label\": 1, \"probability\": 0.0 },\n      { \"className\": \"hyena\", \"label\": 2, \"probability\": 0.0 },\n      { \"className\": \"lion\", \"label\": 3, \"probability\": 0.0 },\n      { \"className\": \"tiger\", \"label\": 4, \"probability\": 0.009999999776482582 },\n      { \"className\": \"wolf\", \"label\": 5, \"probability\": 0.0 }\n    ],\n    \"topPrediction\": {\n      \"className\": \"cheetah\",\n      \"label\": 0,\n      \"probability\": 0.9900000095367432\n    }\n  },\n  \"success\": true\n}\n```\n\n### GraphQL endpoint\n\nGraphQL endpoint is served at `http://localhost:3001/graphql` sending a graphql request at this endpoint with an image file for example as follows using `cURL`:\n\n```shell\ncurl http://localhost:3001/graphql -F operations='{ \"query\": \"mutation ClassifyWildAnimal($input: WildAnimalInput!) { classifyWildAnimal(input: $input) { error { field message } ok prediction { topPrediction {  label probability className } predictions {  label probability className } } } }\", \"variables\": { \"input\": {\"image\": null} } }'  -F map='{ \"0\": [\"variables.input.image\"] }'  -F 0=@cheetah.png\n```\n\nWill yield the results that looks as follows:\n\n```json\n{\n  \"data\": {\n    \"classifyWildAnimal\": {\n      \"error\": null,\n      \"ok\": true,\n      \"prediction\": {\n        \"predictions\": [\n          {\n            \"className\": \"cheetah\",\n            \"label\": 0,\n            \"probability\": 0.9700000286102295\n          },\n          { \"className\": \"fox\", \"label\": 1, \"probability\": 0.0 },\n          {\n            \"className\": \"hyena\",\n            \"label\": 2,\n            \"probability\": 0.009999999776482582\n          },\n          { \"className\": \"lion\", \"label\": 3, \"probability\": 0.0 },\n          {\n            \"className\": \"tiger\",\n            \"label\": 4,\n            \"probability\": 0.029999999329447746\n          },\n          { \"className\": \"wolf\", \"label\": 5, \"probability\": 0.0 }\n        ],\n        \"topPrediction\": {\n          \"className\": \"cheetah\",\n          \"label\": 0,\n          \"probability\": 0.9700000286102295\n        }\n      }\n    }\n  }\n}\n```\n\n### Notebooks\n\nThe notebooks for training the model that is being used to perform image classification on wild animals is found [here](https://github.com/CrispenGari/cv-torch/blob/main/04_WILD_ANIMAL_CLASSIFICATION/01_WILD_ANIMAL_CLASSIFICATION.ipynb).\n\n### License\n\nIn this simple AI tool i'm using `MIT` license which read as follows:\n\n```shell\nMIT License\n\nCopyright (c) 2022 crispengari\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcrispengari%2Fwac","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcrispengari%2Fwac","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcrispengari%2Fwac/lists"}