[{"data":1,"prerenderedAt":53},["ShallowReactive",2],{"workflow-visual-defect-detection":3},{"id":4,"title":5,"cleanup":6,"contributors":10,"deploy":12,"description":15,"diagram":16,"extension":17,"framework":18,"gitHub":19,"introBox":28,"level":32,"meta":33,"resources":34,"s3URL":40,"services":41,"simplicity":44,"stem":45,"testing":46,"type":50,"usecase":51,"videoId":27,"__hash__":52},"workflows\u002Fworkflows\u002Fvisual-defect-detection.json","Visual Defect Detection",{"headline":7,"text":8},"Cleanup",[9],"1. Delete the stack: \u003Ccode>sam delete\u003C\u002Fcode>.",[11],"content\u002Fcontributors\u002Fchengling-saw.json",{"text":13},[14],"sam deploy --guided","Detect anomalies in an image with Amazon Lookout for Vision","\u002Fassets\u002Fimages\u002Fworkflows\u002Fvisual-defect-detection.png","json","AWS SAM",{"template":20,"payloads":25},{"repoURL":21,"templateDir":22,"templateFile":23,"ASL":24},"https:\u002F\u002Fgithub.com\u002Faws-samples\u002Fstep-functions-workflows-collection\u002Ftree\u002Fmain\u002Flookout-for-vision-inference-sam\u002F","lookout-for-vision-inference-sam","template.yaml","statemachine\u002Fstatemachine.asl.json",[26],{"headline":27,"payloadURL":27},"",{"headline":29,"text":30},"How it works",[31],"This workflow demonstrates how to use Step Functions to orchestrate the detection of anomalies in an image uploaded to an Amazon S3 bucket with Amazon Lookout for Vision. ","200",{},{"headline":35,"bullets":36},"Additional resources",[37],{"text":38,"link":39},"Amazon Lookout for Vision Sample","https:\u002F\u002Fgithub.com\u002Faws-samples\u002Famazon-lookout-for-vision",null,[42,43],"s3","lambda","3 - Application","workflows\u002Fvisual-defect-detection",{"headline":47,"text":48},"Testing",[49],"See the GitHub repo for detailed testing instructions.","Standard","Machine Learning","R3yGRzDapQ9hvC0V4wFiNPG0NZCnbNxBOhZ7iWVgu_k",1778846889713]