ruslanchikbundyuk/VTON-API
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Add at new repo again

Browse Source
This commit is contained in:
Руслан Бундюк
2025-01-28 21:48:35 +00:00
commit 6e660ddb3c
564 changed files with 75575 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/README.md Normal file
View File

@@ -0,0 +1 @@
These are quick configs for performance or accuracy regression tracking purposes.

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_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]]

11
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/cascade_mask_rcnn_R_50_FPN_instant_test.yaml Normal file
View File

@@ -0,0 +1,11 @@
_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

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/fast_rcnn_R_50_FPN_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_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]]

15
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/fast_rcnn_R_50_FPN_instant_test.yaml Normal file
View File

@@ -0,0 +1,15 @@
_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

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/keypoint_rcnn_R_50_FPN_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_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]]

14
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/keypoint_rcnn_R_50_FPN_instant_test.yaml Normal file
View File

@@ -0,0 +1,14 @@
_BASE_: "../Base-RCNN-FPN.yaml"
MODEL:
WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
KEYPOINT_ON: True
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

30
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/keypoint_rcnn_R_50_FPN_normalized_training_acc_test.yaml Normal file
View File

@@ -0,0 +1,30 @@
_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]]

28
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/keypoint_rcnn_R_50_FPN_training_acc_test.yaml Normal file
View File

@@ -0,0 +1,28 @@
_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]]

18
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_C4_GCV_instant_test.yaml Normal file
View File

@@ -0,0 +1,18 @@
_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

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_C4_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_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]]

14
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_C4_instant_test.yaml Normal file
View File

@@ -0,0 +1,14 @@
_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

22
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_C4_training_acc_test.yaml Normal file
View File

@@ -0,0 +1,22 @@
_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]]

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_DC5_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_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]]

10
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_FPN_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,10 @@
_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

14
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_FPN_instant_test.yaml Normal file
View File

@@ -0,0 +1,14 @@
_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

21
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/mask_rcnn_R_50_FPN_training_acc_test.yaml Normal file
View File

@@ -0,0 +1,21 @@
_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", 42.0, 1.6], ["segm", "AP", 35.4, 1.25]]

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/panoptic_fpn_R_50_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_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]]

19
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/panoptic_fpn_R_50_instant_test.yaml Normal file
View File

@@ -0,0 +1,19 @@
_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

20
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/panoptic_fpn_R_50_training_acc_test.yaml Normal file
View File

@@ -0,0 +1,20 @@
_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", 38.73, 0.7], ["sem_seg", "mIoU", 64.73, 1.2], ["panoptic_seg", "PQ", 48.13, 0.8]]

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/retinanet_R_50_FPN_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_BASE_: "../COCO-Detection/retinanet_R_50_FPN_3x.yaml"
MODEL:
WEIGHTS: "detectron2://COCO-Detection/retinanet_R_50_FPN_3x/137849486/model_final_4cafe0.pkl"
DATASETS:
TEST: ("coco_2017_val_100",)
TEST:
EXPECTED_RESULTS: [["bbox", "AP", 44.36, 0.02]]

13
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/retinanet_R_50_FPN_instant_test.yaml Normal file
View File

@@ -0,0 +1,13 @@
_BASE_: "../COCO-Detection/retinanet_R_50_FPN_1x.yaml"
MODEL:
WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
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

7
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/rpn_R_50_FPN_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,7 @@
_BASE_: "../COCO-Detection/rpn_R_50_FPN_1x.yaml"
MODEL:
WEIGHTS: "detectron2://COCO-Detection/rpn_R_50_FPN_1x/137258492/model_final_02ce48.pkl"
DATASETS:
TEST: ("coco_2017_val_100",)
TEST:
EXPECTED_RESULTS: [["box_proposals", "AR@1000", 58.16, 0.02]]

13
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/rpn_R_50_FPN_instant_test.yaml Normal file
View File

@@ -0,0 +1,13 @@
_BASE_: "../COCO-Detection/rpn_R_50_FPN_1x.yaml"
MODEL:
WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
DATASETS:
TRAIN: ("coco_2017_val_100",)
TEST: ("coco_2017_val_100",)
SOLVER:
STEPS: (30,)
MAX_ITER: 40
BASE_LR: 0.005
IMS_PER_BATCH: 4
DATALOADER:
NUM_WORKERS: 2

10
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/semantic_R_50_FPN_inference_acc_test.yaml Normal file
View File

@@ -0,0 +1,10 @@
_BASE_: "../Base-RCNN-FPN.yaml"
MODEL:
META_ARCHITECTURE: "SemanticSegmentor"
WEIGHTS: "detectron2://semantic_R_50_FPN_1x/111802073/model_final_c18079783c55a94968edc28b7101c5f0.pkl"
RESNETS:
DEPTH: 50
DATASETS:
TEST: ("coco_2017_val_100_panoptic_stuffonly",)
TEST:
EXPECTED_RESULTS: [["sem_seg", "mIoU", 39.53, 0.02], ["sem_seg", "mACC", 51.50, 0.02]]

18
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/semantic_R_50_FPN_instant_test.yaml Normal file
View File

@@ -0,0 +1,18 @@
_BASE_: "../Base-RCNN-FPN.yaml"
MODEL:
META_ARCHITECTURE: "SemanticSegmentor"
WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
RESNETS:
DEPTH: 50
DATASETS:
TRAIN: ("coco_2017_val_100_panoptic_stuffonly",)
TEST: ("coco_2017_val_100_panoptic_stuffonly",)
INPUT:
MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
SOLVER:
BASE_LR: 0.005
STEPS: (30,)
MAX_ITER: 40
IMS_PER_BATCH: 4
DATALOADER:
NUM_WORKERS: 2

20
vton-api/preprocess/humanparsing/mhp_extension/detectron2/configs/quick_schedules/semantic_R_50_FPN_training_acc_test.yaml Normal file
View File

@@ -0,0 +1,20 @@
_BASE_: "../Base-RCNN-FPN.yaml"
MODEL:
META_ARCHITECTURE: "SemanticSegmentor"
WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
RESNETS:
DEPTH: 50
DATASETS:
TRAIN: ("coco_2017_val_panoptic_stuffonly",)
TEST: ("coco_2017_val_panoptic_stuffonly",)
SOLVER:
BASE_LR: 0.01
WARMUP_FACTOR: 0.001
WARMUP_ITERS: 300
STEPS: (5500,)
MAX_ITER: 7000
TEST:
EXPECTED_RESULTS: [["sem_seg", "mIoU", 76.51, 1.0], ["sem_seg", "mACC", 83.25, 1.0]]
INPUT:
# no scale augmentation
MIN_SIZE_TRAIN: (800, )