Summary

• [x] I have read CONTRIBUTING.md to understand how to contribute to this repository :)

<Please summarize what you are trying to achieve, what changes you made, and how they acheive the desired result.>

What This Is

This is comprehensive documentation for AugLy with Sphinx docstring formatting under the hood with a Read the Docs theme to make augmentation parameters, return types, etc more readable and user-friendly.

How It Works

Sphinx is a documentation generator commonly used by the Python community. It also has its own docstring format.

Internal AugLy docstrings utilize tags such as @param or @returns for labeling due to internal Facebook convention. However, Sphinx does not recognize these tags, opting for : in favor of @, among other changes.

Luckily for us, Python docstring format epytext is very similar to AugLy (credit @Cloud9c), meaning that we can claim that we use epytext formatting and then convert it to sphinx when necessary.

Another problem: Sphinx requires explicit types labeled in the form of :type and :rtype to display types once documentation is rendered. However, Python typehints (which AugLy uses generously) are not natively supported. Therefore we use an extension to Sphinx that autodetects typehints and adds them on the fly.

In the end, Sphinx uses the module structure specified in docs/source with rST (filetype similar to Markdown) to generate a table of contents for our final documentation.

How to Build Documentation Locally

1. Clone repository. git clone github.com/facebookresearch/AugLy
2. Install all requirements for both the library and documentation-specific dependencies cd docs && pip install -r requirements.txt
3. Make sure you are in the docs subdirectory. Then run make html to generate documentation. If you want to delete all these later, you can run make clean.
4. Navigate to docs/build and open index.html

Generating new documentation later

1. Sphinx can detect new files added to the augly subdirectory and add their .rst files accordingly, but the process of detection needs to be triggered manually. Run sphinx-apidoc -o ./source ../augly in the root directory to do so, and update the toctree in index.rst if necessary.
2. Edited a docstring and want to see the same changes be reflected in the published documentation? No worries, this will be automatically completed, an overview of which is provided below.

Integration with ReadTheDocs

1. This documentation uses Sphinx's ReadTheDocs theme to make it easy to publish documentation on RTD's site.
2. Create a Github webhook to detect pushes made to the repository so documentation can rebuild.
3. The .readthedocs.yml file specifies the configuration for these builds. By default ffmpeg and libsndfile1 are based on C and are required as prerequisites before requirements in docs/requirements.txt are installed (as RTD uses Ubuntu behind the scenes).
4. Docstrings aren't stored in the docs subdirectory at all, so all are read from the source folder. Updating the docstrings in augly/<modality> will be sufficient.

Summary

• [x] I have read CONTRIBUTING.md to understand how to contribute to this repository :)

Added randomness to RandomEmojiOverlay parameters like emoji_size. A motivation is that I wanted to randomly change the parameters on-the-fly, rather than "fixed" like current implementation. This modified augmentation was actually used in ISC21 Descriptor Track 1st-place solution.

Test Results

The tests are passed except the following error.

Traceback (most recent call last):
  File "/Users/shuhei.yokoo/Documents/AugLy/augly/tests/image_tests/transforms_unit_test.py", line 177, in test_RandomEmojiOverlay
    self.evaluate_class(
  File "/Users/shuhei.yokoo/Documents/AugLy/augly/tests/image_tests/base_unit_test.py", line 129, in evaluate_class
    are_equal_images(dst, ref), "Expected and outputted images do not match"
  File "/Users/shuhei.yokoo/Documents/AugLy/augly/tests/image_tests/base_unit_test.py", line 20, in are_equal_images
    return a.size == b.size and np.allclose(np.array(a), np.array(b))
  File "<__array_function__ internals>", line 5, in allclose
  File "/Users/shuhei.yokoo/.pyenv/versions/augly/lib/python3.8/site-packages/numpy/core/numeric.py", line 2249, in allclose
    res = all(isclose(a, b, rtol=rtol, atol=atol, equal_nan=equal_nan))
  File "<__array_function__ internals>", line 5, in isclose
  File "/Users/shuhei.yokoo/.pyenv/versions/augly/lib/python3.8/site-packages/numpy/core/numeric.py", line 2358, in isclose
    return within_tol(x, y, atol, rtol)
  File "/Users/shuhei.yokoo/.pyenv/versions/augly/lib/python3.8/site-packages/numpy/core/numeric.py", line 2339, in within_tol
    return less_equal(abs(x-y), atol + rtol * abs(y))
ValueError: operands could not be broadcast together with shapes (1080,1920,3) (1080,1920,4) 

----------------------------------------------------------------------
Ran 71 tests in 35.609s

FAILED (errors=1, skipped=4)
sys:1: ResourceWarning: unclosed file <_io.BufferedReader name='/Users/shuhei.yokoo/Documents/AugLy/augly/assets/tests/image/inputs/dfdc_1.jpg'>

It seems that expected image has alpha channel whereas output image doesn't have alpha channel. I'm not sure why it happened. Replacing the expected image is needed?

Summary

• [X ] I have read CONTRIBUTING.md to understand how to contribute to this repository :)

<Please summarize what you are trying to achieve, what changes you made, and how they acheive the desired result.> I am trying to speed up horizontally flipping, and what I did is use VidGear to execute an ffmpeg command with the preset of ultrafast.

With my changes in running HFlip tests: 4.724 seconds (tests would complete around 2.5 seconds) Without my changes in running HFlip tests: 12.534 seconds (tests would complete around 10.5 seconds)

I've run each test with and without my changes five times on fish shell with this command time for i in (seq 5); python -m unittest augly.tests.video_tests.transforms.ffmpeg_test.TransformsVideoUnitTest.test_HFlip;; end

Unit Tests

If your changes touch the audio module, please run all of the audio tests and paste the output here. Likewise for image, text, & video. If your changes could affect behavior in multiple modules, please run the tests for all potentially affected modules. If you are unsure of which modules might be affected by your changes, please just run all the unit tests.

Audio

python -m unittest discover -s augly/tests/audio_tests/ -p "*"

Image

python -m unittest discover -s augly/tests/image_tests/ -p "*_test.py"
# Or `python -m unittest discover -s augly/tests/image_tests/ -p "*.py"` to run pytorch test too (must install `torchvision` to run)

Text

python -m unittest discover -s augly/tests/text_tests/ -p "*"

Video

python -m unittest discover -s augly/tests/video_tests/ -p "*"

All

python -m unittest discover -s augly/tests/ -p "*"

Other testing

If applicable, test your changes and paste the output here. For example, if your changes affect the requirements/installation, then test installing augly in a fresh conda env, then make sure you are able to import augly & run the unit test

I tried to use the audio augmentations in a tensorflow project but I had a "Segmentation fault" error in running time while importing the modules. In my case it can be reproduced only running these two lines:

import tensorflow
import augly.audio as audaugs

Versions:

tensorflow-gpu==2.4.1
augly==0.1.1
Python 3.8.5

Thank you

Related Issue

Fixes #{128}

Summary

• [x] I have read CONTRIBUTING.md to understand how to contribute to this repository :)
• [x] Add src_mode arg to ret_and_save_image() in image/utils/utils.py
• [x] Pass src_mode arg into ret_and_save_image() from every augmentation except convert_color in image/functional.py (e.g. here for apply_lambda)
• [x] In image test evaluate_class(), assert that the mode of self.img & dst are equal.
• [x] Run image tests, make sure they all pass: python -m unittest discover -s augly/tests/image_tests/ -p "*"

Unit Tests

If your changes touch the audio module, please run all of the audio tests and paste the output here. Likewise for image, text, & video. If your changes could affect behavior in multiple modules, please run the tests for all potentially affected modules. If you are unsure of which modules might be affected by your changes, please just run all the unit tests.

Image

python -m unittest discover -s augly/tests/image_tests/ -p "*_test.py"
# Or `python -m unittest discover -s augly/tests/image_tests/ -p "*.py"` to run pytorch test too (must install `torchvision` to run)

Test Output: n/a

Other testing

N/A

Summary

• [x] I have read CONTRIBUTING.md to understand how to contribute to this repository :)

Computes the bbox that encloses a white box in a black background for any augmentation.

Image

python -m unittest discover -s augly/tests/image_tests/ -p "*_test.py"
# Or `python -m unittest discover -s augly/tests/image_tests/ -p "*.py"` to run pytorch test too (must install `torchvision` to run)

Ran 82 tests in 53.014s

OK (skipped=5)

Other testing

Colab notebook testing the bbox helper → https://colab.research.google.com/drive/1g_0I6f_bv4Wsna6l9jjZrOJ62a4dpu8U#scrollTo=yUczCe6FU9Bs

Summary: Now our files are all correctly formatted for black, and thus we can run black on our files during code review & not have a million irrelevant changes!

Followed the steps here: https://fb.prod.workplace.com/groups/pythonfoundation/posts/2990917737888352/

• Removed aml/augly/ from list of dirs excluded from black formatting in fbsource/tools/arcanist/lint/fbsource-lint-engine.toml
• Ran arc lint --take BLACK --apply-patches --paths-cmd 'hg files aml/augly/'
• Fixed type issues in aml/augly/text/fb/augmenters/back_translate/ which were causing linter errors (there were pyre-ignore comments but they were no longer on the correct line post-black, so just added an assert & initialized a var so we no longer need them)
• Made changes to TARGETS files suggested by linter (moving imports/changing from where some libraries were imported)

Differential Revision: D31526814

Summary

• [x] I have read CONTRIBUTING.md to understand how to contribute to this repository :)

The current method for rotating bounding boxes was bugged because it rotated the bounding box in the wrong direction. This simple sign change fixes it.

Test case: https://github.com/juliusfrost/AugLy/blob/rotate-bounding-box-jupyter/examples/test_rotate.ipynb

Unit Tests

Passes unit tests.

Summary

• [x] I have read CONTRIBUTING.md to understand how to contribute to this repository :)

Summary: Refactored resize() from image/functional.py to be on par with torchvision. However, I just have one minor failure in my code. Please advise on where I should look :)

Test results The following results were acquired from my machine

• Augly original (without interpolation)= 0.04475s
• Augly revised (with interpolation) = 0.02873s
• torchvision (uses interpolation) = 0.02696s

Test code → https://colab.research.google.com/drive/14-KZdSGaOaz73OgIS0DZZY4RsS3cJ0rg#scrollTo=xVI_h-1v49lC

Unit Tests

If your changes touch the audio module, please run all of the audio tests and paste the output here. Likewise for image, text, & video. If your changes could affect behavior in multiple modules, please run the tests for all potentially affected modules. If you are unsure of which modules might be affected by your changes, please just run all the unit tests.

### Image
```bash
python -m unittest discover -s augly/tests/image_tests/ -p "*_test.py"
# Or `python -m unittest discover -s augly/tests/image_tests/ -p "*.py"` to run pytorch test too (must install `torchvision` to run)

TEST OUTPUT

======================================================================
FAIL: test_Resize (transforms_unit_test.TransformsImageUnitTest)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Users/macbookpro/Desktop/Github/AugLy/augly/tests/image_tests/transforms_unit_test.py", line 187, in test_Resize
    self.evaluate_class(imaugs.Resize(), fname="resize")
  File "/Users/macbookpro/Desktop/Github/AugLy/augly/tests/image_tests/base_unit_test.py", line 111, in evaluate_class
    self.assertTrue(
AssertionError: False is not true

----------------------------------------------------------------------
Ran 82 tests in 52.735s

FAILED (failures=1, skipped=5)

🐛 Bug

To Reproduce

Steps to reproduce the behavior:

1. OverlayText with a combination of specific text [166, 287] and specific font (NotoSansBengaliUI-Regular.ttf") results in error.
2. It appears that even if these two characters (with indices 166 and 287) are separated by any number of other characters, it results in the same error.

# imports
import os
import augly.image as imaugs
import augly.utils as utils
from IPython.display import display

# import paths
from augly.utils.base_paths import (
    EMOJI_DIR,
    FONTS_DIR,
    SCREENSHOT_TEMPLATES_DIR,
)

# read sample input_img
input_img_path = os.path.join(
    utils.TEST_URI, "image", "inputs", "dfdc_1.jpg"
)
input_img = imaugs.scale(input_img_path, factor=0.2)

# This results in error
overlay_text = imaugs.OverlayText(
    text = [166, 287],
    font_file = os.path.join(FONTS_DIR, "NotoSansBengaliUI-Regular.ttf"),
)
overlay_text(input_image)

# These do not result in error
overlay_text = imaugs.OverlayText(
    text = [166],
    font_file = os.path.join(FONTS_DIR, "NotoSansBengaliUI-Regular.ttf"),
)
overlay_text(input_image)

# These do not result in error
overlay_text = imaugs.OverlayText(
    text = [287],
    font_file = os.path.join(FONTS_DIR, "NotoSansBengaliUI-Regular.ttf"),
)
overlay_text(input_image)

# These do not result in error
overlay_text = imaugs.OverlayText(
    text = [166, 287]
   # font_file not specified
)
overlay_text(input_image)

Stack trace:

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-74-a3f6c232cffd> in <module>
      3     font_file = os.path.join(FONTS_DIR, "NotoSansBengaliUI-Regular.ttf"),
      4 )
----> 5 overlay_text(input_image)

~/miniconda3/envs/mds572/lib/python3.7/site-packages/augly/image/transforms.py in __call__(self, image, force, metadata)
     48             return image
     49 
---> 50         return self.apply_transform(image, metadata)
     51 
     52     def apply_transform(

~/miniconda3/envs/mds572/lib/python3.7/site-packages/augly/image/transforms.py in apply_transform(self, image, metadata)
    920             x_pos=self.x_pos,
    921             y_pos=self.y_pos,
--> 922             metadata=metadata,
    923         )
    924 

~/miniconda3/envs/mds572/lib/python3.7/site-packages/augly/image/functional.py in overlay_text(image, output_path, text, font_file, font_size, opacity, color, x_pos, y_pos, metadata)
   1121         text=text_str,
   1122         fill=(color[0], color[1], color[2], round(opacity * 255)),
-> 1123         font=font,
   1124     )
   1125 

~/miniconda3/envs/mds572/lib/python3.7/site-packages/PIL/ImageDraw.py in text(self, xy, text, fill, font, anchor, spacing, align, direction, features, language, stroke_width, stroke_fill, embedded_color, *args, **kwargs)
    461             else:
    462                 # Only draw normal text
--> 463                 draw_text(ink)
    464 
    465     def multiline_text(

~/miniconda3/envs/mds572/lib/python3.7/site-packages/PIL/ImageDraw.py in draw_text(ink, stroke_width, stroke_offset)
    416                     ink=ink,
    417                     *args,
--> 418                     **kwargs,
    419                 )
    420                 coord = coord[0] + offset[0], coord[1] + offset[1]

~/miniconda3/envs/mds572/lib/python3.7/site-packages/PIL/ImageFont.py in getmask2(self, text, mode, fill, direction, features, language, stroke_width, anchor, ink, *args, **kwargs)
    668         """
    669         size, offset = self.font.getsize(
--> 670             text, mode, direction, features, language, anchor
    671         )
    672         size = size[0] + stroke_width * 2, size[1] + stroke_width * 2

OSError: unknown freetype error

Expected behavior

I don't know why this combination of text and font does not work. I would expect there to be no error, since overlaying the same text using another font file does not result in error.

Environment

• AugLy Version (e.g., 0.1.2): 0.1.5
• OS (e.g., Linux): Ubuntu 20.04
• How you installed AugLy (pip install augly, clone & pip install -e AugLy): pip install augly
• Python version: 3.7.9
• Other relevant packages (Tensorflow, etc):

Additional context

Same error message can be reproduced using the following combinations as well: text [449, 262] with font file NotoSansThaana-Regular.ttf text [295, 481] with font file NotoSansBengali-Regular.ttf

Related Issue

Fixes N/A

Summary

• [x] I have read CONTRIBUTING.md to understand how to contribute to this repository :)

<Please summarize what you are trying to achieve, what changes you made, and how they acheive the desired result.> Speeding up highpassfilter by taking advantage of existing dependencies

Previous runtime: 1.686479s New runtime: 0.045012s

Unit Tests

If your changes touch the audio module, please run all of the audio tests and paste the output here. Likewise for image, text, & video. If your changes could affect behavior in multiple modules, please run the tests for all potentially affected modules. If you are unsure of which modules might be affected by your changes, please just run all the unit tests.

Audio

python -m unittest discover -s augly/tests/audio_tests/ -p "*"
......./home/adityaprasad/.local/lib/python3.8/site-packages/librosa/util/utils.py:2099: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this w
arning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  np.dtype(np.float): np.complex,
/home/adityaprasad/.local/lib/python3.8/site-packages/librosa/util/utils.py:2099: DeprecationWarning: `np.complex` is a deprecated alias for the builtin `complex`. To silence this warn
ing, use `complex` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.complex128` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  np.dtype(np.float): np.complex,
/home/adityaprasad/.local/lib/python3.8/site-packages/librosa/util/utils.py:869: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning,
use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  mag = np.abs(S).astype(np.float)
........../home/adityaprasad/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:1223: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence
this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  time_steps = np.arange(0, D.shape[1], rate, dtype=np.float)
/home/adityaprasad/.local/lib/python3.8/site-packages/librosa/util/utils.py:2099: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning,
 use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  np.dtype(np.float): np.complex,
/home/adityaprasad/.local/lib/python3.8/site-packages/librosa/util/utils.py:2099: DeprecationWarning: `np.complex` is a deprecated alias for the builtin `complex`. To silence this warn
ing, use `complex` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.complex128` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  np.dtype(np.float): np.complex,
/home/adityaprasad/.local/lib/python3.8/site-packages/librosa/core/spectrum.py:1223: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warni
ng, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  time_steps = np.arange(0, D.shape[1], rate, dtype=np.float)
/home/adityaprasad/.local/lib/python3.8/site-packages/librosa/util/utils.py:869: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning,
use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  mag = np.abs(S).astype(np.float)
..................................................
----------------------------------------------------------------------
Ran 67 tests in 5.665s

OK

If applicable, test your changes and paste the output here. For example, if your changes affect the requirements/installation, then test installing augly in a fresh conda env, then make sure you are able to import augly & run the unit test

🚀 Feature

As i was going thru AugLy i didn't found anything that can paraphrase a sentence and can create 2-3 sentence from 1 as xlnet does in nlpaug library. If it is already available in AugLy can you please mention the same?

Motivation

As i have less data to train. So Augmentation with paraphrasing will help me create more data and will let me train the model.

Pitch

I want one sentence to be paraphrase in how many number of sentence i want. For example if i give n=3, Function should produce 3 sentences from 1 sentence which have similar meaning(paraphrased basically)

Hi AugLy team, Thanks for the great package!

I have seen your comparison with other libs in the paper and have to highlight a missing point: in the table below, pixelization is not compared with an alternative from albumentations.

My guess is you didn't find one, so may I suggest looking at https://albumentations.ai/docs/api_reference/augmentations/transforms/#albumentations.augmentations.transforms.Downscale? It does pixelization using the default params.

Summary: Fixing a pattern of failures where ffmpeg fails when the transition duration is too short.

Refactored the concatenation (no transition effect) in a separate function. Shifting to concatenation when the transition duration is below 0.5 seconds (chosen empirically).

Differential Revision: D37737241

1 Issues

When I use Augly to perform data enhancement operations on videos, I encounter this problem：

Compression Mode is disabled, Kindly enable it to access this function.

But I have installed ffmpeg and configured the environment. Then I tried to debug the code and found a bug.

When the function add_augmenter() calls WriteGear()，The value of parameter custom_ffmpeg is not specified. But later in the code, it is necessary to use its real value:

Line 215 in writegear.py:
    
            self.__ffmpeg = get_valid_ffmpeg_path(
                custom_ffmpeg,
                self.__os_windows,
                ffmpeg_download_path=__ffmpeg_download_path,
                logging=self.__logging,
            )

So that in function get_valid_ffmpeg_path(), the value returned is always False, which causes the program to fail to get the locally downloaded ffmpeg package and must download it again.

Line 885 in helper.py:

def get_valid_ffmpeg_path(
    custom_ffmpeg="", is_windows=False, ffmpeg_download_path="", logging=False
):
    """
    ## get_valid_ffmpeg_path

    Validate the given FFmpeg path/binaries, and returns a valid FFmpeg executable path.

    Parameters:
        custom_ffmpeg (string): path to custom FFmpeg executables
        is_windows (boolean): is running on Windows OS?
        ffmpeg_download_path (string): FFmpeg static binaries download location _(Windows only)_
        logging (bool): enables logging for its operations

    **Returns:** A valid FFmpeg executable path string.
    """
    final_path = ""
    if is_windows:
        # checks if current os is windows
        if custom_ffmpeg:
            # if custom FFmpeg path is given assign to local variable
            final_path += custom_ffmpeg
        else:
            # otherwise auto-download them
            try:
                if not (ffmpeg_download_path):
                    # otherwise save to Temp Directory
                    import tempfile

                    ffmpeg_download_path = tempfile.gettempdir()

                logging and logger.debug(
                    "FFmpeg Windows Download Path: {}".format(ffmpeg_download_path)
                )

                # download Binaries
                os_bit = (
                    ("win64" if platform.machine().endswith("64") else "win32")
                    if is_windows
                    else ""
                )
                _path = download_ffmpeg_binaries(
                    path=ffmpeg_download_path, os_windows=is_windows, os_bit=os_bit
                )
                # assign to local variable
                final_path += _path

2 Solution

Giving the path to the local ffmpeg package when use get_valid_ffmpeg_path(). Like this:

 self.__ffmpeg = get_valid_ffmpeg_path(
                "D:/workSoftware/anaconda/envs/augly/Library/bin/",
                self.__os_windows,
                ffmpeg_download_path=__ffmpeg_download_path,
                logging=self.__logging,
            )

Its path can be obtained using the following method：

import distutils
distutils.spawn.find_executable('ffmpeg')

This way you won't need to reinstall the ffmpeg package every time you use it.

Hi, Is there any data enhancement for the following image, which looks like a mosaic, I used pixelation, but it doesn't look like this kind of corruption.

Thank you !

🚀 Feature

Can the augmentations track keypoints through transformations? I see you have support for bounding boxes, so is it possible to set the bounding box as a single coordinate and track it?

Motivation

Landmark Localization.

Pitch

Track x,y coordinates through transformations.