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align=\"center\"\u003e\u003ca href=\"https://optidash.ai\"\u003e\u003cimg src=\"media/logotype.png\" alt=\"Optidash\" width=\"143\" height=\"45\"/\u003e\u003c/a\u003e\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\nOptidash is a modern, AI-powered image optimization and processing API.\u003cbr\u003eWe will drastically speed-up your websites and save you money on bandwidth and storage.\n\u003c/p\u003e\n\n---\n\u003cp align=\"center\"\u003e\n\u003cstrong\u003eThe official Go integration for the Optidash API.\u003c/strong\u003e\u003cbr\u003e\n\u003cbr\u003e\n\u003cimg src=\"https://img.shields.io/github/issues-raw/optidash-ai/optidash-go?style=flat\u0026color=success\"/\u003e\n\u003cimg src=\"https://img.shields.io/github/license/optidash/optidash-go?style=flat\u0026color=success\"/\u003e\n\u003cimg src=\"https://img.shields.io/twitter/follow/optidashAI?label=Follow%20Us\u0026style=flat\u0026color=success\u0026logo=twitter\"/\u003e\n\u003c/p\u003e\n\n---\n\n### Documentation\nSee the [Optidash API docs](https://docs.optidash.ai).\n\n### Installation\n```bash\n$ go get github.com/optidash-ai/optidash-go\n```\n\n### Quick examples\nOptidash API enables you to provide your images for optimization and processing in two ways - by uploading them directly to the API ([Image Upload](https://docs.optidash.ai/requests/image-upload)) or by providing a publicly available image URL ([Image Fetch](https://docs.optidash.ai/requests/image-fetch)).\n\nYou may also choose your preferred [response method](https://docs.optidash.ai/introduction#choosing-response-method-and-format) on a per-request basis. By default, the Optidash API will return a [JSON response](https://docs.optidash.ai/responses/json-response-format) with rich metadata pertaining to input and output images. Alternatively, you can use [binary responses](https://docs.optidash.ai/responses/binary-responses). When enabled, the API will respond with a full binary representation of the resulting (output) image. This Go integration exposes two convenience methods for interacting with binary responses: `.toFile()` and `.toBuffer()`.\n\n#### Image upload\nHere is a quick example of uploading a local file for processing. It calls `.toJSON()` at a final step and instructs the API to return a JSON response.\n\n```go\npackage main\n\nimport (\n    \"fmt\"\n    \"github.com/optidash-ai/optidash-go\"\n)\n\nfunc main() {\n    // Pass your Optidash API Key to the constructor\n    opti, err := optidash.NewClient(\"your-api-key\")\n\n    if err != nil {\n        panic(err)\n    }\n\n    // Upload an image from disk, resize it to 100 x 75,\n    // automatically enhance, and adjust sharpness parameter.\n    meta, err := opti.\n        Upload(\"path/to/input.jpg\").\n        Optimize(optidash.P{\n            \"compression\": \"medium\"\n        }).\n        Resize(optidash.P{\n            \"width\": 100,\n            \"height\": 75\n        }).\n        Auto(optidash.P{\n            \"enhance\": true\n        }).\n        Adjust(optidash.P{\n            \"unsharp\": 10\n        }).\n        ToJSON()\n\n    if err != nil {\n        panic(err)\n    }\n\n    // You'll find the full JSON metadata within the `meta` variable\n}\n```\n\n#### Image fetch\nIf you already have your source visuals publicly available online, we recommend using Image Fetch by default. That way you only have to send a JSON payload containing image URL and processing steps. This method is also much faster than uploading a full binary representation of the image.\n\n```go\npackage main\n\nimport (\n    \"fmt\"\n    \"github.com/optidash-ai/optidash-go\"\n)\n\nfunc main() {\n    // Pass your Optidash API Key to the constructor\n    opti, err := optidash.NewClient(\"your-api-key\")\n\n    if err != nil {\n        panic(err)\n    }\n\n    // Provide a publicly available image URL with `fetch()` method,\n    // apply Gaussian blur using highly optimized PNG as the output format.\n    // We'll also use `toFile()` method and stream the output image to disk\n    meta, err := opti.\n        Fetch(\"https://www.website.com/image.jpg\").\n        Optimize(optidash.P{\n            \"compression\": \"medium\"\n        }).\n        Filter(optidash.P{\n            \"blur\": optidash.P{\n                \"mode\": \"gaussian\",\n                \"value\": 10\n            }\n        }).\n        Output(optidash.P{\n            \"format\": \"png\"\n        }).\n        ToFile(\"path/to/output.png\")\n\n    if err != nil {\n        panic(err)\n    }\n\n    // You'll find the full JSON metadata within the `meta` variable\n}\n```\n\n### License\nThis software is distributed under the MIT License. See the [LICENSE](LICENSE) file for more information.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foptidash-ai%2Foptidash-go","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foptidash-ai%2Foptidash-go","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foptidash-ai%2Foptidash-go/lists"}