Jar_detection_cv/ml_engine_stuff at master · dashagurova/Jar_detection_cv · GitHub

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NOTES ON TRAINING WITH GCP ML ENGINE


##Things you need on bucket:
model checkpoints
config file
label.pbtxt
train and validation tf.records
packaged code to run on cloud

##MODEL
wget http://storage.googleapis.com/download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_coco_11_06_2017.tar.gz
tar -xvf faster_rcnn_resnet101_coco_11_06_2017.tar.gz
gsutil cp faster_rcnn_resnet101_coco_11_06_2017/model.ckpt.* gs://${YOUR_GCS_BUCKET}/data/


gcloud ml-engine jobs submit training "pets2classes2" \
    --runtime-version 1.9 \
    --job-dir=gs://pets2class/model_dir \
    --packages dist/object_detection-0.1.tar.gz,slim/dist/slim-0.1.tar.gz,/tmp/pycocotools/pycocotools-2.0.tar.gz \
    --module-name object_detection.model_main \
    --region us-central1 \
    --config object_detection/samples/cloud/cloud.yml \
    -- \
    --model_dir=gs://pets2class/model_dir \
    --pipeline_config_path=gs://pets2class/data/pets2class.config

##Config file
sed -i "s|PATH_TO_BE_CONFIGURED|"${BUCKET}"/data|g" \
    object_detection/samples/configs/faster_rcnn_inception_resnet_v2_atrous_oid.config
gsutil cp object_detection/samples/configs/faster_rcnn_inception_resnet_v2_atrous_oid.config \
    ${BUCKET}/data/

/object_detection/samples/configs/faster_rcnn_inception_resnet_v2_atrous_oid.config


## To pack api
bash object_detection/dataset_tools/create_pycocotools_package.sh /tmp/pycocotools
python setup.py sdist
(cd slim && python setup.py sdist)

gcloud ml-engine jobs submit training random_cats1 \
    --job-dir=gs://pet_rand/model_dir \
    --packages dist/object_detection-0.1.tar.gz,slim/dist/slim-0.1.tar.gz,/tmp/pycocotools/pycocotools-2.0.tar.gz \
    --module-name object_detection.model_main \
    --region us-central1 \
    --config object_detection/samples/cloud/cloud.yml \
    -- \
    --model_dir=gs://pet_rand/model_dir \
    --pipeline_config_path=gs://pet_rand/data/faster_rcnn_resnet101_pets.config


gsutil cp gs://${YOUR_GCS_BUCKET}/model_dir/model.ckpt-${CHECKPOINT_NUMBER}.* .
python object_detection/export_inference_graph.py \
    --input_type image_tensor \
    --pipeline_config_path object_detection/samples/configs/faster_rcnn_resnet101_pets.config \
    --trained_checkpoint_prefix rand_cats/model.ckpt-595 \
    --output_directory rand_cats

gsutil cp gs://pet_rand/model_dir/model.ckpt-$995.* .
python object_detection/export_inference_graph.py \
    --input_type image_tensor \
    --pipeline_config_path object_detection/samples/configs/faster_rcnn_resnet101_pets.config \
    --trained_checkpoint_prefix model.ckpt-995 \
    --output_directory exported_graphs


##To mount the extra disk:
	##only when need to erase disk --> sudo mkfs.ext4 -m 0 -F -E lazy_itable_init=0,lazy_journal_init=0,discard /dev/sdb
	sudo mkdir -p /mnt/disks/oid200;\
	sudo mount -o discard,defaults /dev/sdb /mnt/disks/oid200; \
	sudo chmod a+w /mnt/disks/oid200

python -m object_detection/dataset_tools/create_oid_tf_record \
  --input_box_annotations_csv /mnt/disks/oid200/2017_07/train/annotations-human-bbox.csv \
  --input_images_directory /mnt/disks/oid200/train_0 \
  --input_label_map object_detection/data/oid_bbox_trainable_label_map.pbtxt \
  --output_tf_record_path_prefix /mnt/disks/oid200/tfrec_train/train.tfrecord \
  --num_shards=100 \
  --logs="/mnt/disks/oid200/train1.log" \
  --process=1 \
  --num_process=11

END=5
for ((i=0;i<END;i++)); do
    echo $i
	python -m object_detection/dataset_tools/create_oid_tf_record \
  	--input_box_annotations_csv /mnt/disks/oid200/2017_07/train/annotations-human-bbox.csv \
  	--input_images_directory /mnt/disks/oid200/train_0 \
  	--input_label_map object_detection/data/oid_bbox_trainable_label_map.pbtxt \
  	--output_tf_record_path_prefix /mnt/disks/oid200/tfrec_train/train.tfrecord \
  	--num_shards=100 \
  	--logs="/mnt/disks/oid200/logs/train$i.log" \
  	--process=$i \
  	--num_process=END &
done

echo {0..11} | xargs -n 1 echo | parallel -I % \
python -m object_detection/dataset_tools/create_oid_tf_record \
  --input_box_annotations_csv /mnt/disks/oid200/2017_07/train/annotations-human-bbox.csv \
  --input_images_directory /mnt/disks/oid200/train_0 \
  --input_label_map object_detection/data/oid_bbox_trainable_label_map.pbtxt \
  --output_tf_record_path_prefix /mnt/disks/oid200/tfrec_train/train.tfrecord \
  --num_shards=100 \
  --logs="/mnt/disks/oid200/logs/train%.log" \
  --process=% \
  --num_process=12