Replication Data for: First gradually, then suddenly: Understanding the impact of image compression on object detection using deep learning
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This collection contains the object detection results of 9 architectures found in the Detectron2 library, for the MS COCO val2017 dataset, under different compresion level Q = 1, 2, …, 100. The stored results include all detections above 0.5 confidence score threshold, and allows for re-calculation of the performance metrics.There are 9 per-model archive files, and each file contains 100 subfolders named evaluator_dump_&lt;model_name&gt;_&lt;quality&gt;, with results for a particular compression quality for that model. Each folder contains the following files:results.json.gz - summarized performance metrics, overall and per-classcoco_instances_results.json.gz - detailed results for each image, with object classes and bounding boxes.The last file, baseline_05.tar.gz ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["deep learning","jpeg compression","object detection"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This collection contains the object detection results of 9 architectures found in the Detectron2 library, for the MS COCO val2017 dataset, under different compresion level Q = 1, 2, …, 100. The stored results include all detections above 0.5 confidence score threshold, and allows for re-calculation of the performance metrics.There are 9 per-model archive files, and each file contains 100 subfolders named evaluator_dump_&lt;model_name&gt;_&lt;quality&gt;, with results for a particular compression quality for that model. Each folder contains the following files:results.json.gz - summarized performance metrics, overall and per-classcoco_instances_results.json.gz - detailed results for each image, with object classes and bounding boxes.The last file, baseline_05.tar.gz ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This collection contains the object detection results of 9 architectures found in the Detectron2 library, for the MS COCO val2017 dataset, under different compresion level Q = 1, 2, …, 100. The stored results include all detections above 0.5 confidence score threshold, and allows for re-calculation of the performance metrics.There are 9 per-model archive files, and each file contains 100 subfolders named evaluator_dump_&lt;model_name&gt;_&lt;quality&gt;, with results for a particular compression quality for that model. Each folder contains the following files:results.json.gz - summarized performance metrics, overall and per-classcoco_instances_results.json.gz - detailed results for each image, with object classes and bounding boxes.The last file, baseline_05.tar.gz 
deep learning; jpeg compression; object detection