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wmcnally / kapao

KAPAO is an efficient single-stage human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
GNU General Public License v3.0
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What is "gain = torch.ones(7 + self.num_coords * 3 // 2, device=targets.device)" #62

Open omiderfanmanesh opened 2 years ago

omiderfanmanesh commented 2 years ago

Hi I am trying to run this code with my dataset. My dataset was built with the COCO annotator and it has a coco JSON format file. I have one class "gate" and 4 key points. this is my config file:


# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
path: /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco
labels: kp_labels
train: kp_labels/img_txt/train2017.txt
val: kp_labels/img_txt/val2017.txt
test: kp_labels/img_txt/test2017.txt

train_annotations: /home/omid/OMID/projects/python/draft/kapao/utils/Dataset-6.json
val_annotations: /home/omid/OMID/projects/python/draft/kapao/utils/Dataset-6.json
test_annotations: /home/omid/OMID/projects/python/draft/kapao/utils/Dataset-6.json

pose_obj: False  # write pose object labels

nc: 5  # number of classes (person class + 17 keypoint classes)
num_coords: 8  # number of keypoint coordinates (x, y)

# class names
names: [ "gate","top-left", "top-right", "bottom-left", "bottom-right" ]

kp_bbox: 0.05  # keypoint object size (normalized by longest img dim)
kp_flip: []  # for left-right keypoint flipping
kp_left: []  # left keypoints
kp_face: []

kp_names_short:
  0: 'tl'
  1: 'tr'
  2: 'bl'
  3: 'br'

# segments for plotting
segments:
    1: [1, 2]
    2: [1, 3]
    3: [2, 4]
    4: [3, 4]

I create label txt files with utils/labels.py and an example of the file is :

0 0.518229 0.469444 0.555208 0.744444
1 0.289583 0.148611 0.050000 0.066667
2 0.757292 0.181944 0.050000 0.066667
3 0.261458 0.770833 0.050000 0.066667
4 0.723958 0.806944 0.050000 0.066667

The problem is when I want to run the code with these configs and labels, I see this error:


train.py --img 1280 --batch 8 --epochs 500 --data data/coco-kp-draft.yaml --hyp data/hyps/hyp.kp-p6.yaml --val-scales 1 --val-flips -1 --weights yolov5s6.pt --project runs/s_e500 --name train
train: weights=yolov5s6.pt, cfg=, data=data/coco-kp-draft.yaml, hyp=data/hyps/hyp.kp-p6.yaml, epochs=500, batch_size=8, imgsz=1280, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, evolve=None, bucket=, cache=None, image_weights=False, device=, multi_scale=False, single_cls=False, adam=False, sync_bn=False, workers=8, project=runs/s_e500, entity=None, name=train, exist_ok=False, quad=False, linear_lr=False, label_smoothing=0.0, upload_dataset=False, bbox_interval=-1, save_period=-1, artifact_alias=latest, local_rank=-1, freeze=0, patience=100, val_scales=[1.0], val_flips=[-1], autobalance=False
YOLOv5 🚀 ad507c2 torch 1.9.1+cu102 CUDA:0 (NVIDIA GeForce RTX 2070, 7982.3125MB)

hyperparameters: lr0=0.01, lrf=0.2, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.3, cls_pw=1.0, obj=0.7, obj_pw=1.0, kp=0.025, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.9, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, kp_bbox=0.05
TensorBoard: Start with 'tensorboard --logdir runs/s_e500', view at http://localhost:6006/
wandb: Currently logged in as: omiderfanmanesh-altran (use `wandb login --relogin` to force relogin)
wandb: wandb version 0.12.17 is available!  To upgrade, please run:
wandb:  $ pip install wandb --upgrade

wandb: Tracking run with wandb version 0.12.6
wandb: Syncing run train
wandb:  View project at https://wandb.ai/omiderfanmanesh-altran/s_e500
wandb:  View run at https://wandb.ai/omiderfanmanesh-altran/s_e500/runs/35g86hmu
wandb: Run data is saved locally in /home/omid/OMID/projects/python/draft/kapao/wandb/run-20220527_103431-35g86hmu
wandb: Run `wandb offline` to turn off syncing.
Overriding model.yaml nc=80 with nc=13

                 from  n    params  module                                  arguments                     
  0                -1  1      3520  models.common.Focus                     [3, 32, 3]                    
  1                -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                
  2                -1  1     18816  models.common.C3                        [64, 64, 1]                   
  3                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               
  4                -1  3    156928  models.common.C3                        [128, 128, 3]                 
  5                -1  1    295424  models.common.Conv                      [128, 256, 3, 2]              
  6                -1  3    625152  models.common.C3                        [256, 256, 3]                 
  7                -1  1    885504  models.common.Conv                      [256, 384, 3, 2]              
  8                -1  1    665856  models.common.C3                        [384, 384, 1]                 
  9                -1  1   1770496  models.common.Conv                      [384, 512, 3, 2]              
 10                -1  1    656896  models.common.SPP                       [512, 512, [3, 5, 7]]         
 11                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          
 12                -1  1    197376  models.common.Conv                      [512, 384, 1, 1]              
 13                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          
 14           [-1, 8]  1         0  models.common.Concat                    [1]                           
 15                -1  1    813312  models.common.C3                        [768, 384, 1, False]          
 16                -1  1     98816  models.common.Conv                      [384, 256, 1, 1]              
 17                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          
 18           [-1, 6]  1         0  models.common.Concat                    [1]                           
 19                -1  1    361984  models.common.C3                        [512, 256, 1, False]          
 20                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              
 21                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          
 22           [-1, 4]  1         0  models.common.Concat                    [1]                           
 23                -1  1     90880  models.common.C3                        [256, 128, 1, False]          
 24                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              
 25          [-1, 20]  1         0  models.common.Concat                    [1]                           
 26                -1  1    296448  models.common.C3                        [256, 256, 1, False]          
 27                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              
 28          [-1, 16]  1         0  models.common.Concat                    [1]                           
 29                -1  1    715008  models.common.C3                        [512, 384, 1, False]          
 30                -1  1   1327872  models.common.Conv                      [384, 384, 3, 2]              
 31          [-1, 12]  1         0  models.common.Concat                    [1]                           
 32                -1  1   1313792  models.common.C3                        [768, 512, 1, False]          
 33  [23, 26, 29, 32]  1     69336  models.yolo.Detect                      [13, [[19, 27, 44, 40, 38, 94], [96, 68, 86, 152, 180, 137], [140, 301, 303, 264, 238, 542], [436, 615, 739, 380, 925, 792]], [128, 256, 384, 512]]
Model Summary: 368 layers, 12409752 parameters, 12409752 gradients, 16.8 GFLOPs

Transferred 464/472 items from yolov5s6.pt
Scaled weight_decay = 0.0005
optimizer: SGD with parameter groups 77 weight, 81 weight (no decay), 81 bias
albumentations: Blur(always_apply=False, p=0.1, blur_limit=(3, 7)), MedianBlur(always_apply=False, p=0.1, blur_limit=(3, 7)), ToGray(always_apply=False, p=0.01)
train: Scanning '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/kp_labels/img_txt/train2017.cache' images and labels... 164 found, 0 missing, 0 empty, 36 corrupted: 100% 200/200 [00:00<?, ?it/s]
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-45.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-45.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-38.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-38.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-40.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-40.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-41.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-41.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-44.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-44.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-39.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-39.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-07.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-07.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-46.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-46.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-49.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-49.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-02.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-02.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-15.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-15.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-04.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-04.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-05.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-05.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-06.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-06.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-54.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-54.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-10.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-10.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-33.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-33.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-48.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-48.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-50.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-36-50.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-17.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-17.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-38.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-38.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-13.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-13.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-19.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-19.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-20.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-20.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-46.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-46.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-30.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-30.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-32.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-32.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-34.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-34.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-09.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-09.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-37.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-37.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-11.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-11.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-35.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-35.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-41.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-41.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-45.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-45.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-44.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-44.bmp'
train: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-21.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/train2017/2021-12-09_13-37-21.bmp'
val: Scanning '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/kp_labels/img_txt/val2017.cache' images and labels... 164 found, 0 missing, 0 empty, 36 corrupted: 100% 200/200 [00:00<?, ?it/s]
val: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/val2017/2021-12-09_13-36-40.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/val2017/2021-12-09_13-36-40.bmp'
val: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/val2017/2021-12-09_13-36-41.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/val2017/2021-12-09_13-36-41.bmp'
val: WARNING: Ignoring corrupted image and/or label /home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/val2017/2021-12-09_13-36-39.bmp: [Errno 2] No such file or directory: '/home/omid/OMID/projects/python/draft/kapao/data/datasets/front_background1/coco/images/val2017/2021-12-09_13-36-39.bmp'
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autoanchor: Analyzing anchors... anchors/target = 6.07, Best Possible Recall (BPR) = 1.0000
Image sizes 1280 train, 1280 val
Using 8 dataloader workers
Logging results to runs/s_e500/train33
Starting training for 500 epochs...

     Epoch   gpu_mem       box       obj       cls       kps    labels  img_size
  0% 0/21 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "/home/omid/OMID/projects/python/draft/kapao/train.py", line 601, in <module>
    main(opt)
  File "/home/omid/OMID/projects/python/draft/kapao/train.py", line 499, in main
    train(opt.hyp, opt, device)
  File "/home/omid/OMID/projects/python/draft/kapao/train.py", line 315, in train
    loss, loss_items = compute_loss(pred, targets.to(device))  # loss scaled by batch_size
  File "/home/omid/OMID/projects/python/draft/kapao/utils/loss.py", line 133, in __call__
    tcls, tbox, tkps, indices, anchors = self.build_targets(p, targets)  # targets
  File "/home/omid/OMID/projects/python/draft/kapao/utils/loss.py", line 222, in build_targets
    t = targets * gain
RuntimeError: The size of tensor a (7) must match the size of tensor b (19) at non-singleton dimension 2
matt-deboer commented 2 years ago

I ran into the same issue (custom dataset with 20 kps).

It looks like you're setting pose_obj: False in your config--but from my examination of the build_targets method in the loss function, that code path doesn't seem to be supported/possible.

Once I modified my labels to include keypoints in each object instance (as per labels.py) and set pose_obj back to True, the issue was resolved.

Also, if any of your keypoints have v == 0 , be sure to set the x-y coords to (0, 0) (instead of (-1,-1) as is common)--dataset validation will invalidate any negative values in labels.

omiderfanmanesh commented 2 years ago

I ran into the same issue (custom dataset with 20 kps).

It looks like you're setting pose_obj: False in your config--but from my examination of the build_targets method in the loss function, that code path doesn't seem to be supported/possible.

Once I modified my labels to include keypoints in each object instance (as per labels.py) and set pose_obj back to True, the issue was resolved.

Also, if any of your keypoints have v == 0 , be sure to set the x-y coords to (0, 0) (instead of (-1,-1) as is common)--dataset validation will invalidate any negative values in labels.

Thank you for your comment. If I set pose_obj: False to True, the problem is it will generate 17 columns in labels.

wmcnally commented 2 years ago

You may need to modify utils/labels.py to create the label txt files for your custom dataset. I will work on uploading a tutorial for custom training.