tf-imagenet

The challenge

https://www.kaggle.com/c/imagenet-object-localization-challenge

To do

• Upload all images to Google cloud storage
• Create some plumbing for training/eval and testing
• Create a model
• Write a csv-tfrecord converter
• Write tfrecord generator from list of files (for test images)
• Write a submission formatter

Datasets

Type	Size
Train	544,547
Validation	50,000
Test	100,000

• All images are contained in the ILSVRC bucket under ~/ILSVRC/Data/CLS-LOC/[train|val|test]/<wnid>/<wnid>_<count>.JPEG.
• Description for training/val each image can be found in LOC_[train|val]_solution.csv.

Sample LOC_*_solution record

ILSVRC2012_val_00008726,n02119789 255 142 454 329 n02119789 44 21 322 295

The above is interpreted as:

• Describes image ~/ILSVRC/Data/CLS-LOC/val/ILSVRC2012_val_00049992.JPEG
• Two objects are labeled in that image:
  • Object n02119789, with bounding box at (255, 142) and (454, 329)
  • Object n02119789, with bounding box at (44, 21) and (322, 295)

A mapping of all 1,000 classes to be detected is found in LOC_synset_mapping.txt.