catvton

detectron2/model_zoo/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_inference_acc_test.yaml

+_BASE_: "../Misc/cascade_mask_rcnn_R_50_FPN_3x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://Misc/cascade_mask_rcnn_R_50_FPN_3x/144998488/model_final_480dd8.pkl"
+DATASETS:
+  TEST: ("coco_2017_val_100",)
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 50.18, 0.02], ["segm", "AP",  43.87, 0.02]]

detectron2/model_zoo/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_instant_test.yaml

+_BASE_: "../Misc/cascade_mask_rcnn_R_50_FPN_3x.yaml"
+DATASETS:
+  TRAIN: ("coco_2017_val_100",)
+  TEST: ("coco_2017_val_100",)
+SOLVER:
+  BASE_LR: 0.005
+  STEPS: (30,)
+  MAX_ITER: 40
+  IMS_PER_BATCH: 4
+DATALOADER:
+  NUM_WORKERS: 2

detectron2/model_zoo/configs/quick_schedules/fast_rcnn_R_50_FPN_inference_acc_test.yaml

+_BASE_: "../COCO-Detection/fast_rcnn_R_50_FPN_1x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://COCO-Detection/fast_rcnn_R_50_FPN_1x/137635226/model_final_e5f7ce.pkl"
+DATASETS:
+  TEST: ("coco_2017_val_100",)
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 45.70, 0.02]]

detectron2/model_zoo/configs/quick_schedules/fast_rcnn_R_50_FPN_instant_test.yaml

+_BASE_: "../COCO-Detection/fast_rcnn_R_50_FPN_1x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+DATASETS:
+  TRAIN: ("coco_2017_val_100",)
+  PROPOSAL_FILES_TRAIN: ("detectron2://COCO-Detection/rpn_R_50_FPN_1x/137258492/coco_2017_val_box_proposals_ee0dad.pkl", )
+  TEST: ("coco_2017_val_100",)
+  PROPOSAL_FILES_TEST: ("detectron2://COCO-Detection/rpn_R_50_FPN_1x/137258492/coco_2017_val_box_proposals_ee0dad.pkl", )
+SOLVER:
+  BASE_LR: 0.005
+  STEPS: (30,)
+  MAX_ITER: 40
+  IMS_PER_BATCH: 4
+DATALOADER:
+  NUM_WORKERS: 2

detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_inference_acc_test.yaml

+_BASE_: "../COCO-Keypoints/keypoint_rcnn_R_50_FPN_3x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://COCO-Keypoints/keypoint_rcnn_R_50_FPN_3x/137849621/model_final_a6e10b.pkl"
+DATASETS:
+  TEST: ("keypoints_coco_2017_val_100",)
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 52.47, 0.02], ["keypoints", "AP", 67.36, 0.02]]

detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_instant_test.yaml

+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  KEYPOINT_ON: True
+  ROI_HEADS:
+    NUM_CLASSES: 1
+DATASETS:
+  TRAIN: ("keypoints_coco_2017_val_100",)
+  TEST: ("keypoints_coco_2017_val_100",)
+SOLVER:
+  BASE_LR: 0.005
+  STEPS: (30,)
+  MAX_ITER: 40
+  IMS_PER_BATCH: 4
+DATALOADER:
+  NUM_WORKERS: 2

detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_normalized_training_acc_test.yaml

+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  KEYPOINT_ON: True
+  RESNETS:
+    DEPTH: 50
+  ROI_HEADS:
+    BATCH_SIZE_PER_IMAGE: 256
+    NUM_CLASSES: 1
+  ROI_KEYPOINT_HEAD:
+    POOLER_RESOLUTION: 14
+    POOLER_SAMPLING_RATIO: 2
+    NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: False
+    LOSS_WEIGHT: 4.0
+  ROI_BOX_HEAD:
+    SMOOTH_L1_BETA: 1.0  # Keypoint AP degrades when using plain L1 loss
+  RPN:
+    SMOOTH_L1_BETA: 0.2  # Keypoint AP degrades when using plain L1 loss
+DATASETS:
+  TRAIN: ("keypoints_coco_2017_val",)
+  TEST: ("keypoints_coco_2017_val",)
+INPUT:
+  MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
+SOLVER:
+  WARMUP_FACTOR: 0.33333333
+  WARMUP_ITERS: 100
+  STEPS: (5500, 5800)
+  MAX_ITER: 6000
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 55.35, 1.0], ["keypoints", "AP", 76.91, 1.0]]

detectron2/model_zoo/configs/quick_schedules/keypoint_rcnn_R_50_FPN_training_acc_test.yaml

+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  KEYPOINT_ON: True
+  RESNETS:
+    DEPTH: 50
+  ROI_HEADS:
+    BATCH_SIZE_PER_IMAGE: 256
+    NUM_CLASSES: 1
+  ROI_KEYPOINT_HEAD:
+    POOLER_RESOLUTION: 14
+    POOLER_SAMPLING_RATIO: 2
+  ROI_BOX_HEAD:
+    SMOOTH_L1_BETA: 1.0  # Keypoint AP degrades when using plain L1 loss
+  RPN:
+    SMOOTH_L1_BETA: 0.2  # Keypoint AP degrades when using plain L1 loss
+DATASETS:
+  TRAIN: ("keypoints_coco_2017_val",)
+  TEST: ("keypoints_coco_2017_val",)
+INPUT:
+  MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
+SOLVER:
+  WARMUP_FACTOR: 0.33333333
+  WARMUP_ITERS: 100
+  STEPS: (5500, 5800)
+  MAX_ITER: 6000
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 53.5, 1.0], ["keypoints", "AP", 72.4, 1.0]]

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_GCV_instant_test.yaml

+_BASE_: "../Base-RCNN-C4.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  MASK_ON: True
+DATASETS:
+  TRAIN: ("coco_2017_val_100",)
+  TEST: ("coco_2017_val_100",)
+SOLVER:
+  BASE_LR: 0.001
+  STEPS: (30,)
+  MAX_ITER: 40
+  IMS_PER_BATCH: 4
+  CLIP_GRADIENTS:
+    ENABLED: True
+    CLIP_TYPE: "value"
+    CLIP_VALUE: 1.0
+DATALOADER:
+  NUM_WORKERS: 2

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_inference_acc_test.yaml

+_BASE_: "../COCO-InstanceSegmentation/mask_rcnn_R_50_C4_3x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_C4_3x/137849525/model_final_4ce675.pkl"
+DATASETS:
+  TEST: ("coco_2017_val_100",)
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 47.37, 0.02], ["segm", "AP", 40.99, 0.02]]

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_instant_test.yaml

+_BASE_: "../Base-RCNN-C4.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  MASK_ON: True
+DATASETS:
+  TRAIN: ("coco_2017_val_100",)
+  TEST: ("coco_2017_val_100",)
+SOLVER:
+  BASE_LR: 0.001
+  STEPS: (30,)
+  MAX_ITER: 40
+  IMS_PER_BATCH: 4
+DATALOADER:
+  NUM_WORKERS: 2

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_C4_training_acc_test.yaml

+_BASE_: "../Base-RCNN-C4.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  ROI_HEADS:
+    BATCH_SIZE_PER_IMAGE: 256
+  MASK_ON: True
+DATASETS:
+  TRAIN: ("coco_2017_val",)
+  TEST: ("coco_2017_val",)
+INPUT:
+  MIN_SIZE_TRAIN: (600,)
+  MAX_SIZE_TRAIN: 1000
+  MIN_SIZE_TEST: 800
+  MAX_SIZE_TEST: 1000
+SOLVER:
+  IMS_PER_BATCH: 8  # base uses 16
+  WARMUP_FACTOR: 0.33333
+  WARMUP_ITERS: 100
+  STEPS: (11000, 11600)
+  MAX_ITER: 12000
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 41.88, 0.7], ["segm", "AP", 33.79, 0.5]]

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_DC5_inference_acc_test.yaml

+_BASE_: "../COCO-InstanceSegmentation/mask_rcnn_R_50_DC5_3x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_DC5_3x/137849551/model_final_84107b.pkl"
+DATASETS:
+  TEST: ("coco_2017_val_100",)
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 47.44, 0.02], ["segm", "AP", 42.94, 0.02]]

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_inference_acc_test.yaml

+_BASE_: "../COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl"
+DATASETS:
+  TEST: ("coco_2017_val_100",)
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 47.34, 0.02], ["segm", "AP",  42.67, 0.02], ["bbox_TTA", "AP", 49.11, 0.02], ["segm_TTA", "AP", 45.04, 0.02]]
+  AUG:
+    ENABLED: True
+    MIN_SIZES: (700, 800)  # to save some time

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_instant_test.yaml

+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  MASK_ON: True
+DATASETS:
+  TRAIN: ("coco_2017_val_100",)
+  TEST: ("coco_2017_val_100",)
+SOLVER:
+  BASE_LR: 0.005
+  STEPS: (30,)
+  MAX_ITER: 40
+  IMS_PER_BATCH: 4
+DATALOADER:
+  NUM_WORKERS: 2

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_pred_boxes_training_acc_test.yaml

+_BASE_: "./mask_rcnn_R_50_FPN_training_acc_test.yaml"
+MODEL:
+  ROI_BOX_HEAD:
+    TRAIN_ON_PRED_BOXES: True
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 42.6, 1.0], ["segm", "AP", 35.8, 0.8]]

detectron2/model_zoo/configs/quick_schedules/mask_rcnn_R_50_FPN_training_acc_test.yaml

+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  ROI_HEADS:
+    BATCH_SIZE_PER_IMAGE: 256
+  MASK_ON: True
+DATASETS:
+  TRAIN: ("coco_2017_val",)
+  TEST: ("coco_2017_val",)
+INPUT:
+  MIN_SIZE_TRAIN: (600,)
+  MAX_SIZE_TRAIN: 1000
+  MIN_SIZE_TEST: 800
+  MAX_SIZE_TEST: 1000
+SOLVER:
+  WARMUP_FACTOR: 0.3333333
+  WARMUP_ITERS: 100
+  STEPS: (5500, 5800)
+  MAX_ITER: 6000
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 42.5, 1.0], ["segm", "AP", 35.8, 0.8]]

detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_inference_acc_test.yaml

+_BASE_: "../COCO-PanopticSegmentation/panoptic_fpn_R_50_3x.yaml"
+MODEL:
+  WEIGHTS: "detectron2://COCO-PanopticSegmentation/panoptic_fpn_R_50_3x/139514569/model_final_c10459.pkl"
+DATASETS:
+  TEST: ("coco_2017_val_100_panoptic_separated",)
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 46.47, 0.02], ["segm", "AP", 43.39, 0.02], ["sem_seg", "mIoU", 42.55, 0.02], ["panoptic_seg", "PQ", 38.99, 0.02]]

detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_instant_test.yaml

+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  META_ARCHITECTURE: "PanopticFPN"
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  MASK_ON: True
+  RESNETS:
+    DEPTH: 50
+  SEM_SEG_HEAD:
+    LOSS_WEIGHT: 0.5
+DATASETS:
+  TRAIN: ("coco_2017_val_100_panoptic_separated",)
+  TEST: ("coco_2017_val_100_panoptic_separated",)
+SOLVER:
+  BASE_LR: 0.005
+  STEPS: (30,)
+  MAX_ITER: 40
+  IMS_PER_BATCH: 4
+DATALOADER:
+  NUM_WORKERS: 1

detectron2/model_zoo/configs/quick_schedules/panoptic_fpn_R_50_training_acc_test.yaml

+_BASE_: "../Base-RCNN-FPN.yaml"
+MODEL:
+  META_ARCHITECTURE: "PanopticFPN"
+  WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+  MASK_ON: True
+  RESNETS:
+    DEPTH: 50
+  SEM_SEG_HEAD:
+    LOSS_WEIGHT: 0.5
+DATASETS:
+  TRAIN: ("coco_2017_val_panoptic_separated",)
+  TEST: ("coco_2017_val_panoptic_separated",)
+SOLVER:
+  BASE_LR: 0.01
+  WARMUP_FACTOR: 0.001
+  WARMUP_ITERS: 500
+  STEPS: (5500,)
+  MAX_ITER: 7000
+TEST:
+  EXPECTED_RESULTS: [["bbox", "AP", 46.70, 1.1], ["segm", "AP", 39.0, 0.7], ["sem_seg", "mIoU", 64.73, 1.3], ["panoptic_seg", "PQ", 48.13, 0.8]]