Object Detection

object detection is a computer vision technique used to identify and locate objects within an image or video it involves both classification (identifying what the object is) and localization (identifying where the object is in the image) the below input parameters are for different attack types to start working with the apis view the docid 8dgizrgxboplgxgngdrzu object detection is an early access with limited functionality it is not available in aishield pypi package for early access, kindly contact mailto\ aishield contact\@bosch com file upload format data the processed data, ready to be passed to the model for prediction, should be saved in a folder https //aisdocs blob core windows net/reference/upload/image/objectdetection/data zip label a list of xml files that have the same names as the images in the dataset folder https //aisdocs blob core windows net/reference/upload/image/objectdetection/xml zip model the yolo model should be saved in onnx format and then zipped https //aisdocs blob core windows net/reference/upload/image/objectdetection/model zip note all files uploaded should be in zipped format the above files are sample data for the pascal voc use case prerequisite only 2 5 % of data is needed common parameters the below table parameters are common for all attact types such as extraction, evasion, and poisoning to see the additional parameter specific for each attact type, such as extraction and evasion, refer to the below sections parameter data type description remark model id string model id received during model registration we need to provide this model id in query parameter in url you have to do model registration only once for a model to perform model analysis this will help you track the no of api call made, and it's success metric request body (json format) normalize data string model trained on normalized data i f model is trained on normalized data, then set this parameter as "yes" else "no" model api details string if use model api is yes, then provide api details of hosted model as encrypted json string is mandatory p rovide this only if use model api is "yes" use model api string use model api to train your model instead of uploading the model as a zip use model api to train your model instead of uploading the model as a zip defense bestonly string choose to train your model until it achieves the best results or above 95% accuracy w hen selected "yes" , it will train n number of model and select best model ofcourse this will take longer time if "no" , then once defense model accuracy reached above 95% it will stop model framework string original model is built framework curretly supported framework are onnx to access all sample artifacts, please visit docid\ ijneocxostabvvrsq11fa for specific artifact details, refer vulnerability report docid\ hl0ut2mwlcbkt8f97fr w sample attacks docid 4g1mjm5lqjfm8t5wbvwpr defense report docid\ vtzlttpja2vsf2j0stlsq defense model docid\ xsbxmzxw4vv14 8nmbf8m note for object detection, supported attack types are evasion