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Migrate to project.toml based setuptools
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# this file is *not* meant to cover or endorse the use of GitHub Actions, but rather to | ||
# help test this project | ||
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name: Test | ||
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on: [push, pull_request] | ||
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jobs: | ||
test: | ||
strategy: | ||
matrix: | ||
python: ['3.9', '3.10', '3.11', '3.12'] | ||
platform: [ubuntu-latest, macos-latest, windows-latest] | ||
runs-on: ${{ matrix.platform }} | ||
steps: | ||
- name: Checkout | ||
uses: actions/checkout@v4 | ||
- name: Set up Python ${{ matrix.python }} | ||
uses: actions/setup-python@v5 | ||
with: | ||
python-version: ${{ matrix.python }} | ||
- name: Install test dependencies | ||
run: python -m pip install -U tox | ||
- name: Test | ||
run: python -m tox -e py |
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.pyre/ | ||
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images/ | ||
temp* | ||
temp* | ||
excluded/ |
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# Changelogs | ||
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## v1.2.3 | ||
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<details markdown="1" open> | ||
<summary><i>Click here to show more.</i></summary> | ||
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In this version, we have made the following changes: | ||
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1. 🧬 **CHANGE!**: We change the GUI mode to **optional**. | ||
* Now, you can install the GUI mode by running: | ||
* ```bash | ||
pip install skin-tone-classifier[all] --upgrade | ||
``` | ||
* It will support both the **CLI** mode and the **GUI** mode. | ||
* If you don't specify the `[all]` option, the app will install the CLI mode only. | ||
2. 🧬 **CHANGE!**: [For developer]. We base the project to `project.toml` instead of `setup.py`. | ||
</details> | ||
## v1.2.0 | ||
<details markdown="1" open> | ||
<summary><i>Click here to show more.</i></summary> | ||
In this version, we have made the following changes: | ||
1. ✨ **NEW!**: We add a GUI version of `stone` for users who are not familiar with the command line interface. | ||
* You can use the config GUI of `stone` to process the images. | ||
* See more information at [here](#use-stone-in-a-gui). | ||
2. ✨ **NEW!**: We add new **patterns** in the `-l` (or `--labels`) option to set the skin tone labels. | ||
* Now, you can use the following patterns to set the skin tone labels: | ||
* **Default value**: the uppercase alphabet list leading by the image type (`C` for `color`; `B` | ||
for `Black&White`). | ||
* Specify the labels directly using _a space_ as delimiters, e.g., `-l A B C D E` or `-l 1 2 3 4 5`. | ||
* Specify the range of labels using _a hyphen_ as delimiters, e.g., | ||
* `-l A-E` (equivalent to `-l A B C D E`); | ||
* `-l A-E-2` (equivalent to `-l A C E`); | ||
* `-l 1-5` (equivalent to `-l 1 2 3 4 5`); | ||
* `-l 1-10-3` (equivalent to `-l 1 4 7 10`); | ||
* **NB**: The number of skin tone labels should be equal to the number of colors in the palette. | ||
</details> | ||
## v1.1.2 | ||
<details markdown="1"> | ||
<summary><i>Click here to show more.</i></summary> | ||
In this version, we have made the following changes: | ||
1. 🐛 **FIX!**: We fixed a bug where the app will crash when using the `-bw` option. | ||
Error message: `cannot reshape array of size 62500 into shape (3)`. | ||
2. 🐛 **FIX!**: We fixed a bug where the app may identify the image type as `color` when using the `-bw` option. | ||
</details> | ||
## v1.1.1 | ||
<details markdown="1"> | ||
<summary><i>Click here to show more.</i></summary> | ||
In this version, we have made the following changes: | ||
1. ✨ **NEW!**: We add the `-v` (or `--version`) option to show the version number. | ||
2. ✨ **NEW!**: We add the `-r` (or `--recursive`) option to **enable** recursive search for images. | ||
* For example, `stone -i ./path/to/images/ -r` will search all images in the `./path/to/images/` directory **and its | ||
subdirectories**. | ||
* `stone -i ./path/to/images/` will only search images in the `./path/to/images/` directory. | ||
3. 🐛 **FIX!**: We fixed a bug where the app cannot correctly identify the current folder if `-i` option is not | ||
specified. | ||
</details> | ||
## v1.1.0 | ||
<details markdown="1"> | ||
<summary><i>Click here to show more.</i></summary> | ||
In this version, we have made the following changes: | ||
1. ✨ **NEW!**: Now, `stone` can not only be run on **the command line**, but can also be **imported** into other | ||
projects for use. Check [this](#9-used-as-a-library-by-importing-into-other-projects) for more details. | ||
* We expose the `process` and `show` functions in the `stone` package. | ||
2. ✨ **NEW!**: We add `URL` support for the input images. | ||
* Now, you can specify the input image as a URL, e.g., `https://example.com/images/pic.jpg`. Of course, you can mix | ||
the URLs and local filenames. | ||
3. ✨ **NEW!**: We add **recursive search** support for the input images. | ||
* Now, when you specify the input image as a directory, e.g., `./path/to/images/`. | ||
The app will search all images in the directory recursively. | ||
4. 🧬 **CHANGE!**: We change the column header in `result.csv`: | ||
* `prop` => `percent` | ||
* `PERLA` => `tone label` | ||
5. 🐛 **FIX!**: We fixed a bug where the app would not correctly sort files that did not contain numbers in their | ||
filenames. | ||
</details> | ||
## v1.0.1 | ||
<details markdown="1"> | ||
<summary><i>Click here to show more.</i></summary> | ||
1. 👋 **BYE**: We have removed the function to pop up a resulting window when processing a **single** image. | ||
* It can raise an error when running the app in a **web browser** environment, e.g., Jupyter Notebook or Google | ||
Colab. | ||
* If you want to see the processed image, please use the `-d` option to store the report image in the `./debug` | ||
folder. | ||
</details> | ||
## v1.0.0 | ||
<details markdown="1"> | ||
<summary><i>Click here to show more.</i></summary> | ||
🎉**We have officially released the 1.0.0 version of the library!** In this version, we have made the following changes: | ||
1. ✨ **NEW!**: We add the `threshold` parameter to control the minimum percentage of required face areas (Defaults to | ||
0.15). | ||
* In previous versions, the library could incorrectly identify non-face areas as faces, such as shirts, collars, | ||
necks, etc. | ||
In order to improve its accuracy, the new version will further calculate the proportion of skin in the recognized | ||
area | ||
after recognizing the facial area. If it is less than the `threshold` value, the recognition area will be ignored. | ||
(While it's still not perfect, it's an improvement over what it was before.) | ||
2. ✨ **NEW!**: Now, we will back up the previous results if it already exists. | ||
The backup file will be named as `result_bak_<current_timestamp>.csv`. | ||
3. 🐛 **FIX!**: We fix the bug that the `image_type` option does not work in the previous version. | ||
4. 🐛 **FIX!**: We fix the bug that the library will create an empty `log` folder when checking the help information by | ||
running `stone -h`. | ||
</details> | ||
## v0.2.0 | ||
<details markdown="1"> | ||
<summary><i>Click here to show more.</i></summary> | ||
In this version, we have made the following changes: | ||
1. ✨ **NEW!**: Now we support skin tone classification for **black and white** images. | ||
* In this case, the app will use different skin tone palettes for color images and black/white images. | ||
* We use a new parameter `-t` or `--image_type` to specify the type of the input image. | ||
It can be `color`, `bw` or `auto`(default). | ||
`auto` will let the app automatically detect whether the input is color or black/white image. | ||
* We use a new parameter `-bw` or `--black_white` to specify whether to convert the input to black/white image. | ||
If so, the app will convert the input to black/white image and then classify the skin tones based on the | ||
black/white palette. | ||
For example: | ||
<div style="display: flex; align-items: center;"> | ||
<img src="https://raw.githubusercontent.com/ChenglongMa/SkinToneClassifier/main/docs/demo-1.png" alt="Processing color image" style="display: block; margin: 20px"> | ||
<img src="https://raw.githubusercontent.com/ChenglongMa/SkinToneClassifier/main/docs/demo_bw-1.png" alt="Processing black/white image" style="display: block; margin: 20px"> | ||
</div> | ||
2. ✨ **NEW!**: Now we support **multiprocessing** for processing the images. It will largely speed up the processing. | ||
* The number of processes is set to the number of CPU cores by default. | ||
* You can specify the number of processes by `--n_workers` parameter. | ||
3. 🧬 **CHANGE!**: We add more details in the report image to facilitate the debugging, as shown above. | ||
* We add the face id in the report image. | ||
* We add the effective face or skin area in the report image. In this case, the other areas are blurred. | ||
4. 🧬 **CHANGE!**: Now, we save the report images into different folders based on their `image_type` (color or | ||
black/white) and the number of detected faces. | ||
* For example, if the input image is **color** and there are **2 faces** detected, the report image will be saved | ||
in `./debug/color/faces_2/` folder. | ||
* If the input image is **black/white** and no face has been detected, the report image will be saved | ||
in `./debug/bw/faces_0/` folder. | ||
* You can easily to tune the parameters and rerun the app based on the report images in the corresponding folder. | ||
5. 🐛 **FIX!**: We fix the bug that the app will crash when the input image has dimensionality errors. | ||
* Now, the app won't crash and will report the error message in `./result.csv`. | ||
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</details> |
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