vita-epfl / detection-attributes-fields Goto Github PK

@svenkreiss @taylormordan can we train the whole model for only few classes like the general attributes from 32 to 10 . what all changes have to be made ? so how will be a change in accuracy of the model ?
THanks in advance

@svenkreiss @taylormordan i test the model on certain images , for few images it works well and for others its not work well

1. Bad
   

2. Good

The observation is the nearby person has multiple bounding boxes , pls share your thoughts

Thanks in advance

where is the training script?

Hi @svenkreiss @taylormordan.

Is there a way that we can run decoder on GPU?
Evaluation and Validation is consuming more time during the decoder run as it runs on CPU.

Thanks in Advance

INFO:openpifpaf.network.trainer:{'type': 'train', 'epoch': 65, 'batch': 840, 'n_batches': 1266, 'time': 0.948, 'data_time': 0.0, 'lr': 0.0005, 'loss': -31.85, 'head_losses': [0.003, 0.097, 0.076, 0.111, 0.02, 0.25, 0.016, 0.027, 0.001, 0.0, 0.014, 0.015, 0.026, 0.019, 0.073, 0.021, 0.013, 0.004, 0.0, 0.039, 0.09, 0.088, 0.037, 0.006, 0.0, 0.003, 0.014, 0.003, 0.012, 0.011, 0.002, 0.002, 0.001, 0.002, 0.012], 'mtl_sigmas': [0.002, 0.301, 0.275, 0.367, 0.081, 0.518, 0.089, 0.171, 0.016, 0.0, 0.1, 0.092, 0.124, 0.122, 0.218, 0.046, 0.09, 0.027, 0.0, 0.176, 0.262, 0.26, 0.157, 0.037, 0.0, 0.003, 0.09, 0.003, 0.087, 0.065, 0.006, 0.01, 0.0, 0.002, 0.072]}

is this normal?

usage: python3 -m openpifpaf.train [options]
python3 -m openpifpaf.train: error: unrecognized arguments: --jaad-root-dir C:/Users/VR/Desktop/JAAD_clips.zip --jaad-subset default --jaad-training-set train --jaad-validation-set val --pifpaf-pretraining --detection-bias-prior 0.01 --jaad-head-upsample 2 --jaad-pedestrian-attributes all --fork-normalization-operation power --fork-normalization-duplicates 35 --attribute-regression-loss l1 --attribute-focal-gamma 2

I just gave the path to the output of the model and the data set this way.
Please take a look:

!python3 -m openpifpaf.train
--output C:/Users/VR/Desktop/model
--dataset jaad
--jaad-root-dir C:/Users/VR/Desktop/JAAD_clips.zip
--jaad-subset default
--jaad-training-set train
--jaad-validation-set val
--log-interval 10
--val-interval 1
--epochs 5
--batch-size 4
--lr 0.0005
--lr-warm-up-start-epoch -1
--weight-decay 5e-4
--momentum 0.95
--basenet fn-resnet50
--pifpaf-pretraining
--detection-bias-prior 0.01
--jaad-head-upsample 2
--jaad-pedestrian-attributes all
--fork-normalization-operation power
--fork-normalization-duplicates 35
--lambdas 7.0 7.0 7.0 7.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
--attribute-regression-loss l1
--attribute-focal-gamma 2
--auto-tune-mtl

I found it too slow to train a new model. Can you share a trained model? Thanks a lot.

@svenkreiss @taylormordan thanks for sharing the source code , can we extend this work for car detection with attributes along with person and its attributes , if so how can we do it ? we can annotated vehicle with bounding box and attributes can be brand , #wheels ,color . what all changes have to be made in the source code for extending the source code

Thanks in advance

how's the result and performance?

How can I plot detected attributions on the image?

@taylormordan thanks for sharing the code base and the wonderful work is it possible to share the pretrained model to test the results ??
Thanks in advance

@svenkreiss @taylormordan any idea how to extend this composite fields for segmentation based tasks along with multi label classification of the preson
Please share your thoughts