generate.sh

#!/usr/bin/env bash
# Path to checkpoint file or a directory containing checkpoint files. Passing
# a directory will only work if there is also a file named 'checkpoint' which
# lists the available checkpoints in the directory. It will not work if you
# point to a directory with just a copy of a model checkpoint: in that case,
# you will need to pass the checkpoint path explicitly.
#CHECKPOINT_PATH="/Users/jinu/tensorflow/models/research/im2txt/Pretrained-Show-and-Tell-model/model.ckpt-2000000"

# Vocabulary file generated by the preprocessing script.
#VOCAB_FILE="/Users/jinu/tensorflow/models/research/im2txt/Pretrained-Show-and-Tell-model/word_counts.txt"

# JPEG image file to caption.
# IMAGE_FILE="/Users/jinu/tensorflow/models/research/im2txt/Pretrained-Show-and-Tell-model/images/test.jpg"

# Build the inference binary.
#bazel build -c opt /Users/jinu/tensorflow/models/research/im2txt/run_inference

# Run inference to generate captions.
#/Users/jinu/tensorflow/models/research/im2txt/bazel-bin/im2txt/run_inference \
#  --checkpoint_path=${CHECKPOINT_PATH} \
#  --vocab_file=${VOCAB_FILE} \
#  --input_files=${IMAGE_FILE}

CHECKPOINT_PATH="./deeplearning/im2txt/Pretrained-Show-and-Tell-model/model.ckpt-2000000"

# Vocabulary file generated by the preprocessing script.
VOCAB_FILE="./deeplearning/im2txt/Pretrained-Show-and-Tell-model/word_counts.txt"

# JPEG image file to caption.
IMAGE_FILE="$1"

# Build the inference binary.
bazel build -c opt ./deeplearning/im2txt/run_inference

# Run inference to generate captions.
./deeplearning/im2txt/bazel-bin/im2txt/run_inference \
  --checkpoint_path=${CHECKPOINT_PATH} \
  --vocab_file=${VOCAB_FILE} \
  --input_files=${IMAGE_FILE}