├── LICENSE ├── README.md ├── coco ├── annotations │ ├── instances_train2017.json │ └── instances_val2017.json └── images │ ├── train2017 │ └── 000000391895.jpg │ └── val2017 │ └── 000000397133.jpg ├── config └── config.ini ├── csv ├── annotations.csv ├── classes.csv └── images │ └── 000001.jpg └── pascal ├── Annotations └── 000001.xml ├── ImageSets └── Main │ ├── train.txt │ └── val.txt └── JPEGImages └── 000001.jpg /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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-------------------------------------------------------------------------------- 1 | # keras-retinanet-test-data 2 | Test data for keras-retinanet. 3 | -------------------------------------------------------------------------------- /coco/annotations/instances_train2017.json: -------------------------------------------------------------------------------- 1 | {"info": {"description": "COCO 2017 Dataset", "url": "http://cocodataset.org", "version": "1.0", "year": 2017, "contributor": "COCO Consortium", "date_created": "2017/09/01"}, "licenses": [{"url": "http://creativecommons.org/licenses/by-nc-sa/2.0/", "id": 1, "name": "Attribution-NonCommercial-ShareAlike License"}, {"url": "http://creativecommons.org/licenses/by-nc/2.0/", "id": 2, "name": "Attribution-NonCommercial License"}, {"url": "http://creativecommons.org/licenses/by-nc-nd/2.0/", "id": 3, "name": "Attribution-NonCommercial-NoDerivs License"}, {"url": "http://creativecommons.org/licenses/by/2.0/", "id": 4, "name": "Attribution License"}, {"url": "http://creativecommons.org/licenses/by-sa/2.0/", "id": 5, "name": "Attribution-ShareAlike License"}, {"url": "http://creativecommons.org/licenses/by-nd/2.0/", "id": 6, "name": "Attribution-NoDerivs License"}, {"url": "http://flickr.com/commons/usage/", "id": 7, "name": "No known copyright restrictions"}, {"url": "http://www.usa.gov/copyright.shtml", "id": 8, "name": "United States Government Work"}], "images": [{"license": 3, "file_name": "000000391895.jpg", "coco_url": "http://images.cocodataset.org/train2017/000000391895.jpg", "height": 360, "width": 640, "date_captured": "2013-11-14 11:18:45", "flickr_url": "http://farm9.staticflickr.com/8186/8119368305_4e622c8349_z.jpg", "id": 391895}], "annotations": [{"segmentation": [[376.97, 176.91, 398.81, 176.91, 396.38, 147.78, 447.35, 146.17, 448.16, 172.05, 448.16, 178.53, 464.34, 186.62, 464.34, 192.28, 448.97, 195.51, 447.35, 235.96, 441.69, 258.62, 454.63, 268.32, 462.72, 276.41, 471.62, 290.98, 456.25, 298.26, 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"kitchen", "id": 44, "name": "bottle"}, {"supercategory": "kitchen", "id": 46, "name": "wine glass"}, {"supercategory": "kitchen", "id": 47, "name": "cup"}, {"supercategory": "kitchen", "id": 48, "name": "fork"}, {"supercategory": "kitchen", "id": 49, "name": "knife"}, {"supercategory": "kitchen", "id": 50, "name": "spoon"}, {"supercategory": "kitchen", "id": 51, "name": "bowl"}, {"supercategory": "food", "id": 52, "name": "banana"}, {"supercategory": "food", "id": 53, "name": "apple"}, {"supercategory": "food", "id": 54, "name": "sandwich"}, {"supercategory": "food", "id": 55, "name": "orange"}, {"supercategory": "food", "id": 56, "name": "broccoli"}, {"supercategory": "food", "id": 57, "name": "carrot"}, {"supercategory": "food", "id": 58, "name": "hot dog"}, {"supercategory": "food", "id": 59, "name": "pizza"}, {"supercategory": "food", "id": 60, "name": "donut"}, {"supercategory": "food", "id": 61, "name": "cake"}, {"supercategory": "furniture", "id": 62, "name": "chair"}, {"supercategory": "furniture", "id": 63, "name": "couch"}, {"supercategory": "furniture", "id": 64, "name": "potted plant"}, {"supercategory": "furniture", "id": 65, "name": "bed"}, {"supercategory": "furniture", "id": 67, "name": "dining table"}, {"supercategory": "furniture", "id": 70, "name": "toilet"}, {"supercategory": "electronic", "id": 72, "name": "tv"}, {"supercategory": "electronic", "id": 73, "name": "laptop"}, {"supercategory": "electronic", "id": 74, "name": "mouse"}, {"supercategory": "electronic", "id": 75, "name": "remote"}, {"supercategory": "electronic", "id": 76, "name": "keyboard"}, {"supercategory": "electronic", "id": 77, "name": "cell phone"}, {"supercategory": "appliance", "id": 78, "name": "microwave"}, {"supercategory": "appliance", "id": 79, "name": "oven"}, {"supercategory": "appliance", "id": 80, "name": "toaster"}, {"supercategory": "appliance", "id": 81, "name": "sink"}, {"supercategory": "appliance", "id": 82, "name": "refrigerator"}, {"supercategory": 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{"supercategory": "food", "id": 56, "name": "broccoli"}, {"supercategory": "food", "id": 57, "name": "carrot"}, {"supercategory": "food", "id": 58, "name": "hot dog"}, {"supercategory": "food", "id": 59, "name": "pizza"}, {"supercategory": "food", "id": 60, "name": "donut"}, {"supercategory": "food", "id": 61, "name": "cake"}, {"supercategory": "furniture", "id": 62, "name": "chair"}, {"supercategory": "furniture", "id": 63, "name": "couch"}, {"supercategory": "furniture", "id": 64, "name": "potted plant"}, {"supercategory": "furniture", "id": 65, "name": "bed"}, {"supercategory": "furniture", "id": 67, "name": "dining table"}, {"supercategory": "furniture", "id": 70, "name": "toilet"}, {"supercategory": "electronic", "id": 72, "name": "tv"}, {"supercategory": "electronic", "id": 73, "name": "laptop"}, {"supercategory": "electronic", "id": 74, "name": "mouse"}, {"supercategory": "electronic", "id": 75, "name": "remote"}, {"supercategory": "electronic", "id": 76, "name": "keyboard"}, {"supercategory": "electronic", "id": 77, "name": "cell phone"}, {"supercategory": "appliance", "id": 78, "name": "microwave"}, {"supercategory": "appliance", "id": 79, "name": "oven"}, {"supercategory": "appliance", "id": 80, "name": "toaster"}, {"supercategory": "appliance", "id": 81, "name": "sink"}, {"supercategory": "appliance", "id": 82, "name": "refrigerator"}, {"supercategory": "indoor", "id": 84, "name": "book"}, {"supercategory": "indoor", "id": 85, "name": "clock"}, {"supercategory": "indoor", "id": 86, "name": "vase"}, {"supercategory": "indoor", "id": 87, "name": "scissors"}, {"supercategory": "indoor", "id": 88, "name": "teddy bear"}, {"supercategory": "indoor", "id": 89, "name": "hair drier"}, {"supercategory": "indoor", "id": 90, "name": "toothbrush"}]} -------------------------------------------------------------------------------- /coco/images/train2017/000000391895.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fizyr/keras-retinanet-test-data/98404379fbf1ff1273d01db835c10cc83a4f8007/coco/images/train2017/000000391895.jpg -------------------------------------------------------------------------------- /coco/images/val2017/000000397133.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fizyr/keras-retinanet-test-data/98404379fbf1ff1273d01db835c10cc83a4f8007/coco/images/val2017/000000397133.jpg -------------------------------------------------------------------------------- /config/config.ini: -------------------------------------------------------------------------------- 1 | [anchor_parameters] 2 | # Sizes should correlate to how the network processes an image, it is not advised to change these! 3 | sizes = 32 64 128 256 512 4 | # Strides should correlate to how the network strides over an image, it is not advised to change these! 5 | strides = 8 16 32 64 128 6 | # The different ratios to use per anchor location. 7 | ratios = 0.5 1 2 3 8 | # The different scaling factors to use per anchor location. 9 | scales = 1 1.2 1.6 10 | -------------------------------------------------------------------------------- /csv/annotations.csv: -------------------------------------------------------------------------------- 1 | images/000001.jpg,47,239,194,370,person 2 | -------------------------------------------------------------------------------- /csv/classes.csv: -------------------------------------------------------------------------------- 1 | person,0 2 | -------------------------------------------------------------------------------- /csv/images/000001.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fizyr/keras-retinanet-test-data/98404379fbf1ff1273d01db835c10cc83a4f8007/csv/images/000001.jpg -------------------------------------------------------------------------------- /pascal/Annotations/000001.xml: -------------------------------------------------------------------------------- 1 | 2 | VOC2007 3 | 000001.jpg 4 | 5 | The VOC2007 Database 6 | PASCAL VOC2007 7 | flickr 8 | 341012865 9 | 10 | 11 | Fried Camels 12 | Jinky the Fruit Bat 13 | 14 | 15 | 353 16 | 500 17 | 3 18 | 19 | 0 20 | 21 | dog 22 | Left 23 | 1 24 | 0 25 | 26 | 48 27 | 240 28 | 195 29 | 371 30 | 31 | 32 | 33 | person 34 | Left 35 | 1 36 | 0 37 | 38 | 8 39 | 12 40 | 352 41 | 498 42 | 43 | 44 | 45 | -------------------------------------------------------------------------------- /pascal/ImageSets/Main/train.txt: -------------------------------------------------------------------------------- 1 | 000001 2 | -------------------------------------------------------------------------------- /pascal/ImageSets/Main/val.txt: -------------------------------------------------------------------------------- 1 | 000001 2 | -------------------------------------------------------------------------------- /pascal/JPEGImages/000001.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fizyr/keras-retinanet-test-data/98404379fbf1ff1273d01db835c10cc83a4f8007/pascal/JPEGImages/000001.jpg --------------------------------------------------------------------------------