Skip to content

Update README.md #1

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
EthanSeal wants to merge 1 commit into
base: md-changes
Choose a base branch
from
Open

Update README.md #1

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
15 changes: 8 additions & 7 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,7 @@ To bring in all DVC managed project componenets, run the following command. Note
```
dvc pull
```
Note that you may already have these data in TextbookSegmentationDatasetGenerator, so you could save some disk space by just pathing to that directory in the config file.


## Training
Expand All @@ -55,22 +56,22 @@ There is an option to use a pretrained VGG model. We did not experiment with thi


```
python3 dhSegment/train.py with config.json
python3 dhSegment/train.py with general_config.json
```

If you are training on your own dataset, you will need to adjust data/classes.txt to reflect your dataset.

If you are training on your own dataset, you will need to adjust data/classes.txt to reflect your dataset. We do this for our dataset of novels with our novel_config.json.

## Inference/Visualization

visualize.py will take in a model, an image directory, and an output directory. It will segment each page, then draw the bounding boxes onto the image and export them. It will also export an txt file containing each bounding box's pixel coordinates and an xml file for each image containing the coordinates of each box.
visualize.py will take in a model, an image directory, and an output directory. It will segment each page, then draw the bounding boxes onto the image and export them. It will also export a txt file containing each bounding box's pixel coordinates and an xml file for each image containing the coordinates of each box.

```
python3 dhSegment/visualize.py <model_directory> <image_directory> <output_directory>
```

## Changes from vanilla dhSegment
We added visualize.py, described above.

We moved bb_detection.py from somewhere else in the code to its current location.




We also edited general_config.json to suit the needs of our textbook dataset and we created novel_config.json for our novel dataset.