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# Path to checkpoint file.
# Notice there's no data-00000-of-00001 in the CHECKPOINT_PATH environment variable
# Also make sure you place model.ckpt-2000000.index (which is cloned from the repository)
# in the same location as model.ckpt-2000000.data-00000-of-00001
# You can use model.ckpt-1000000.data-00000-of-00001 similarly
CHECKPOINT_PATH="/path/to/model.ckpt-2000000"
# Vocabulary file generated by the preprocessing script.
# Since the tokenizer could be of a different version, use the word_counts.txt file supplied.
VOCAB_FILE="/path/to/word_counts.txt"
# JPEG image file to caption.
IMAGE_FILE="/path/to/image.jpeg"
# Build the inference binary.
bazel build -c opt im2txt/run_inference
# Run inference to generate captions.
bazel-bin/im2txt/run_inference \
--checkpoint_path=${CHECKPOINT_PATH} \
--vocab_file=${VOCAB_FILE} \
--input_files=${IMAGE_FILE}
Extras
Graph.pbtxt is uploaded on request.
Training stats are uploaded for use with tensorboard. tensorboard --logdir="./extras/tensorboard/"
About
This repository contains pretrained Show and Tell: A Neural Image Caption Generator implemented in Tensorflow.