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xingyizhou / UniDet

Object detection on multiple datasets with an automatically learned unified label space.
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[Learning a unified label space]: FileNotFoundError: [Errno 2] No such file or directory for "json.load(open(unified_label_file, 'r'))" #9

Open jichengyuan opened 3 years ago

jichengyuan commented 3 years ago

Hi,

thank you for this awesome idea on this nice multi-dataset-object-detectror.

I've trained a "Partitioned detector" on coco, oid and obejcts365-V2. (for V2, because MEGVII have updated their dataset, we could not download v1 anymore.)

When I tried the second step: Learning a unified label space: I followed the tutorial and run:

python projects/UniDet/train_net.py \ --config-file projects/UniDet/Partitioned_COI_R50_2x.yaml \ --num-gpus 1 \ --eval-only MULTI_DATASET.UNIFIED_EVAL True

It raised a "FileNotFoundError". When I checked config file, I found that the key "UNIFIED_LABEL_FILE" in the config file has been set as ' ' (None), as shown in images below.

Could you give me some hints about how could I generate this this file or label space?

many thanks!

FileNotFoundError:

fileNotFoundErroe_unified_label

config.yaml:

UNIFIELD_LABEL_FILE

jichengyuan commented 3 years ago

I also tried with the command below for “Learning a unified label space”:

python projects/UniDet/train_net.py \ --config-file projects/UniDet/Partitioned_COI_R50_2x.yaml \ --num-gpus 1 \ --eval-only \ MULTI_DATASET.UNIFIED_EVAL True \ MODEL.WEIGHTS output/UniDet/Partitioned_COI_R50_2x/model_final.pth \ MULTI_DATASET.UNIFIED_LABEL_FILE datasets/label_spaces/manual.json

Then I got very low mAP:

learning_unified_label_space

but when I validated the model as partitioned detectors, it works fine:

python projects/UniDet/train_net.py \ --config projects/UniDet/configs/Partitioned_COI_R50_2x.yaml \ --eval-only \ --num-gpus 1 \ MODEL.WEIGHTS output/UniDet/Partitioned_COI_R50_2x/model_final.pth

partitioned_validation

HXZhong1997 commented 3 years ago

Same question when I tried to train on my two custom datasets. Didn't have a clue yet :cry:

jichengyuan commented 3 years ago

I have checked this file "projects\UniDet\unidet\evaluation\multi_dataset_evaluator.py"

For the "_unified_results", the label_space is a specific one (such as coco) rather than a unified label space.

That means, if we execute an evaluation on coco dataset, the "_unified_results" from the unified detector is same as the the "coco_results" from the partitioned detector.