Tensorflow Slim Imagenet training - tensorflow

Question

I am trying to prepare the date to train an ImageNet model from scratch and I am a bit confused about how the training works.
While preparing the TF records I noticed this file inside the Inception model data directory: "imagenet_metadata.txt". The file holds labels for 21842 classes yet the training script and "imagenet_lsvrc_2015_synsets.txt" file only works for 1000 classes.
I am wondering what modifications I need to do to train the model on the 21K classes not the 1K one?

Answer 1

It's quite straightforward with slim.To Train imgnet 21k with slim I recommend to do the following steps:
1.In tf_models/slim/datasets Folder create a copy of imagenet.py File ( for example imgnet.py).In the new file Change the required
Variables to your desired Values:
_FILE_PATTERN = ####your tfrecord_file_pattern. for me('imgnet_%s_*.tfrecord')
_SPLITS_TO_SIZES = {
'train': ####Training Samples,
'validation': ####Validation Samples,}
_NUM_CLASSES = 21841
*the wordnet synset contains 21482 entries but the total number of classes in imagenet21k in 21481 (n04399382 is missed).so be sure about the total number of available classes.
*Also you need to do a little modification in code in order to load the synset files from your local address.
base_url = '/home/snf/libraries/tf_models/slim'
synset_url = '{}/listOfTags.txt'.format(base_url)
synset_to_human_url = '{}/imagenet21k_metadata.txt'.format(base_url)
Add the new dataset to datasetfactory.py in tf_models/slim/datasets :
from datasets import imgnet
datasets_map = {
'cifar10': cifar10,
'flowers': flowers,
'imagenet': imagenet,
'mnist': mnist,
'imgnet': imgnet, #add this line to dataset_map
}
In tf_models/slim/ create Train_Imgnet.sh File containing these lines:
TRAIN_DIR=trained/imgnet-inception-v4
DATASET_DIR=/media/where/tfrecords/saved/tfRecords-fall11_21k
CUDA_VISIBLE_DEVICES="0,1,2,3" python train_image_classifier.py
--train_dir=${TRAIN_DIR} \
--dataset_name=imgnet \
--dataset_split_name=train \
--dataset_dir=${DATASET_DIR} \
--model_name=inception_v4 \
--max_number_of_steps=10000000 \
--batch_size=32 \
--learning_rate=0.01 \
--learning_rate_decay_type=fixed \
--save_interval_secs=60 \
--save_summaries_secs=60 \
--log_every_n_steps=100 \
--optimizer=rmsprop \
--weight_decay=0.00004\
--num_readers=12 \
--num_clones=4
set the file to executable (Chmod +x Train_Imgnet.sh ) and run it (./Train_Imgnet.sh )