Updates

.gitignore

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+# Created by https://www.toptal.com/developers/gitignore/api/python
+# Edit at https://www.toptal.com/developers/gitignore?templates=python
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### Python Patch ###
+# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
+poetry.toml
+
+# ruff
+.ruff_cache/
+
+# LSP config files
+pyrightconfig.json
+
+# End of https://www.toptal.com/developers/gitignore/api/python
+
+.DS_Store
+.idea
+.vscode

LICENSE.txt

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+Copyright 2023 Andrei Cozma
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.

generate_samples.py

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+import os
+
+import numpy as np
+from PIL import Image
+from scipy.ndimage import gaussian_filter
+
+
+def create_blank_image(size=256):
+    return np.zeros((size, size), dtype=np.uint8)
+
+
+def add_horizontal_lines(image, spacing=10):
+    for i in range(0, image.shape[0], spacing):
+        image[i, :] = 255
+    return image
+
+
+def add_vertical_lines(image, spacing=10):
+    for i in range(0, image.shape[1], spacing):
+        image[:, i] = 255
+    return image
+
+
+def add_diagonal_lines(image, spacing=10):
+    for i in range(0, image.shape[0], spacing):
+        np.fill_diagonal(image[i:, i:], 255)
+    return image
+
+
+# Add a circle to the image
+def add_circle(image, radius=50):
+    center_x, center_y = image.shape[1] // 2, image.shape[0] // 2
+    y, x = np.ogrid[
+        -center_y : image.shape[0] - center_y, -center_x : image.shape[1] - center_x
+    ]
+    mask = x * x + y * y <= radius * radius
+    image[mask] = 255
+    return image
+
+
+def add_checkerboard(image, square_size=16):
+    for i in range(0, image.shape[0], square_size * 2):
+        for j in range(0, image.shape[1], square_size * 2):
+            image[i : i + square_size, j : j + square_size] = 255
+            image[
+                i + square_size : i + square_size * 2,
+                j + square_size : j + square_size * 2,
+            ] = 255
+    return image
+
+
+def add_horizontal_sinusoidal(image, frequency=1 / 20, amplitude=127):
+    x = np.linspace(0, 1, image.shape[1])
+    y = np.sin(2 * np.pi * frequency * x) * amplitude + 128
+    for i in range(image.shape[0]):
+        image[i, :] = y
+    return image
+
+
+def add_vertical_sinusoidal(image, frequency=1 / 20, amplitude=127):
+    x = np.linspace(0, 1, image.shape[0])
+    y = np.sin(2 * np.pi * frequency * x) * amplitude + 128
+    for i in range(image.shape[1]):
+        image[:, i] = y
+    return image
+
+
+def add_random_noise(image, std_dev=50):
+    noise = np.random.normal(0, std_dev, image.shape).astype(np.float32)
+    image = image.astype(np.float32) + noise
+    np.clip(image, 0, 255, out=image)
+    image = image.astype(np.uint8)
+    return image
+
+
+def save_image(image, filename):
+    image = Image.fromarray(image)
+    image.save(filename)
+
+
+savedir = "./images/"
+
+os.makedirs(savedir, exist_ok=True)
+
+save_image(create_blank_image(), savedir + "blank.png")
+save_image(add_horizontal_lines(create_blank_image()), savedir + "horizontal.png")
+save_image(add_vertical_lines(create_blank_image()), savedir + "vertical.png")
+save_image(add_diagonal_lines(create_blank_image()), savedir + "diagonal.png")
+save_image(add_circle(create_blank_image()), savedir + "circle.png")
+save_image(add_checkerboard(create_blank_image()), savedir + "checkerboard.png")
+save_image(
+    add_horizontal_sinusoidal(create_blank_image()),
+    savedir + "horizontal_sinusoidal.png",
+)
+save_image(
+    add_vertical_sinusoidal(create_blank_image()), savedir + "vertical_sinusoidal.png"
+)
+save_image(add_random_noise(create_blank_image()), savedir + "random_noise.png")

main.py

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+import os
+from typing import Tuple, Union
+
+import gradio as gr
+import numpy as np
+from PIL import Image, ImageChops, ImageOps
+
+
+class ImageInfo:
+    def __init__(
+        self,
+        size: Tuple[int, int],
+        channels: int,
+        data_type: str,
+        min_val: float,
+        max_val: float,
+    ):
+        self.size = size
+        self.channels = channels
+        self.data_type = data_type
+        self.min_val = min_val
+        self.max_val = max_val
+
+    @classmethod
+    def from_pil(cls, pil_image: Image.Image) -> "ImageInfo":
+        size = (pil_image.width, pil_image.height)
+        channels = len(pil_image.getbands())
+        data_type = str(pil_image.mode)
+        extrema = pil_image.getextrema()
+        if channels > 1:  # Multi-band image
+            min_val = min([band[0] for band in extrema])
+            max_val = max([band[1] for band in extrema])
+        else:  # Single-band image
+            min_val, max_val = extrema
+        return cls(size, channels, data_type, min_val, max_val)
+
+    @classmethod
+    def from_numpy(cls, np_array: np.ndarray) -> "ImageInfo":
+        if len(np_array.shape) > 3:
+            raise ValueError(f"Unsupported array shape: {np_array.shape}")
+        size = (np_array.shape[1], np_array.shape[0])
+        channels = 1 if len(np_array.shape) == 2 else np_array.shape[2]
+        data_type = str(np_array.dtype)
+        min_val, max_val = np_array.min(), np_array.max()
+        return cls(size, channels, data_type, min_val, max_val)
+
+    @classmethod
+    def from_any(cls, image: Union[Image.Image, np.ndarray]) -> "ImageInfo":
+        if isinstance(image, np.ndarray):
+            return cls.from_numpy(image)
+        elif isinstance(image, Image.Image):
+            return cls.from_pil(image)
+        else:
+            raise ValueError(f"Unsupported image type: {type(image)}")
+
+    def __str__(self) -> str:
+        return f"{str(self.size)} {self.channels}C {self.data_type} {round(self.min_val, 2)}min/{round(self.max_val, 2)}max"
+
+    @property
+    def aspect_ratio(self) -> float:
+        return self.size[0] / self.size[1]
+
+
+def nextpow2(n):
+    """Find the next power of 2 greater than or equal to `n`."""
+    return int(2 ** np.ceil(np.log2(n)))
+
+
+def pad_image_nextpow2(image):
+    print("-" * 80)
+    print("pad_image_nextpow2: ")
+    print(ImageInfo.from_any(image))
+
+    if image.ndim == 2:
+        image = image[:, :, np.newaxis]
+
+    assert image.ndim == 3, f"Expected image.ndim == 3. Got {image.ndim}"
+
+    height, width, channels = image.shape
+    height_new = nextpow2(height)
+    width_new = nextpow2(width)
+
+    height_diff = height_new - height
+    width_diff = width_new - width
+
+    image = np.pad(
+        image,
+        (
+            (height_diff // 2, height_diff - height_diff // 2),
+            (width_diff // 2, width_diff - width_diff // 2),
+            (0, 0),
+        ),
+        mode="constant",
+        # mode="edge",
+        # mode="linear_ramp",
+        # mode="maximum",
+        # mode="mean",
+        # mode="median",
+        # mode="minimum",
+        # mode="reflect",
+        # mode="symmetric",
+        # mode="wrap",
+        # mode="empty",
+    )
+
+    print(ImageInfo.from_any(image))
+
+    return image
+
+
+def get_fft(image):
+    print("-" * 80)
+    print("get_fft: ")
+    print("image:", ImageInfo.from_any(image))
+
+    fft = np.fft.fft2(image, axes=(0, 1, 2))
+    fft = np.fft.fftshift(fft)
+
+    return fft
+
+
+def get_ifft_image(fft):
+    print("-" * 80)
+    print("get_ifft_image: ")
+
+    ifft = np.fft.ifftshift(fft)
+    ifft = np.fft.ifft2(ifft, axes=(0, 1, 2))
+
+    # we only need the real part
+    ifft_image = np.real(ifft)
+
+    # remove padding
+    # ifft = ifft[
+    #     h_diff // 2 : h_diff // 2 + original_shape[0],
+    #     w_diff // 2 : w_diff // 2 + original_shape[1],
+    # ]
+
+    ifft_image = (ifft_image - np.min(ifft_image)) / (
+        np.max(ifft_image) - np.min(ifft_image)
+    )
+    ifft_image = ifft_image * 255
+    ifft_image = ifft_image.astype(np.uint8)
+
+    return ifft_image
+
+
+def fft_mag_image(fft):
+    print("-" * 80)
+    print("fft_mag_image: ")
+
+    fft_mag = np.abs(fft)
+    fft_mag = np.log(fft_mag + 1)
+
+    # scale 0 to 1
+    fft_mag = (fft_mag - np.min(fft_mag)) / (np.max(fft_mag) - np.min(fft_mag) + 1e-6)
+    # scale to (0, 255)
+    fft_mag = fft_mag * 255
+    fft_mag = fft_mag.astype(np.uint8)
+    return fft_mag
+
+
+def fft_phase_image(fft):
+    print("-" * 80)
+    print("fft_phase_image: ")
+
+    fft_phase = np.angle(fft)
+    fft_phase = fft_phase + np.pi
+    fft_phase = fft_phase / (2 * np.pi)
+
+    # scale 0 to 1
+    fft_phase = (fft_phase - np.min(fft_phase)) / (
+        np.max(fft_phase) - np.min(fft_phase)
+    )
+    # scale to (0, 255)
+    fft_phase = fft_phase * 255
+    fft_phase = fft_phase.astype(np.uint8)
+    return fft_phase
+
+
+def onclick_process_fft(state, inp_image, mask_opacity, inverted_mask, pad):
+    print("-" * 80)
+    print("onclick_process_fft:")
+
+    if isinstance(inp_image, dict):
+        if "image" not in inp_image:
+            raise gr.Error("Please upload or select an image first.")
+
+        image, mask = inp_image["image"], inp_image["mask"]
+        print("image:", ImageInfo.from_any(image))
+        print("mask:", ImageInfo.from_any(image))
+
+        image = Image.fromarray(image)
+        mask = Image.fromarray(mask)
+
+        if not inverted_mask:
+            mask = ImageOps.invert(mask)
+
+        image_final = ImageChops.multiply(image, mask)
+        image_final = Image.blend(image, image_final, mask_opacity)
+
+        image_final = image_final.convert(image.mode)
+        image_final = np.array(image_final)
+    elif isinstance(inp_image, np.ndarray):
+        image_final = inp_image
+    else:
+        raise gr.Error("Please upload or select an image first.")
+
+    print("image_final:", ImageInfo.from_any(image_final))
+
+    if pad:
+        image_final = pad_image_nextpow2(image_final)
+
+    state["inp_image"] = image_final
+
+    image_mag = fft_mag_image(get_fft(image_final))
+    image_phase = fft_phase_image(get_fft(image_final))
+
+    return (
+        [
+            (image_final, "Input Image (Final)"),
+            (image_mag, "FFT Magnitude (Original)"),
+            (image_phase, "FFT Phase (Original)"),
+        ],
+        image_mag,
+        image_phase,
+    )
+
+
+def onclick_process_ifft(state, mag_and_mask, phase_and_mask):
+    print("-" * 80)
+    print("onclick_process_ifft:")
+    if state["inp_image"] is None:
+        raise gr.Error("Please process FFT first.")
+
+    image = state["inp_image"]
+    # h_new = nextpow2(original_shape[0])
+    # w_new = nextpow2(original_shape[1])
+    # h_diff = h_new - original_shape[0]
+    # w_diff = w_new - original_shape[1]
+
+    mask_mag = mag_and_mask["mask"]
+    print("mag_mask:", ImageInfo.from_any(mask_mag))
+
+    mask_phase = phase_and_mask["mask"]
+    print("phase_mask:", ImageInfo.from_any(mask_phase))
+
+    fft = get_fft(state["inp_image"])
+    print(f"fft: {fft.shape}")
+
+    fft_mag = np.where(mask_mag == 255, 0, np.abs(fft))
+    fft_phase = np.where(mask_phase == 255, 0, np.angle(fft))
+
+    fft = fft_mag * np.exp(1j * fft_phase)
+
+    ifft_image = get_ifft_image(fft)
+    image_mag = fft_mag_image(fft)
+    image_phase = fft_phase_image(fft)
+
+    return (
+        [
+            (image, "Input Image (Final)"),
+            (image_mag, "FFT Magnitude (Filtered)"),
+            (image_phase, "FFT Phase (Filtered)"),
+        ],
+        ifft_image,
+    )
+
+
+def get_start_image():
+    return (np.ones((512, 512, 3)) * 255).astype(np.uint8)
+
+
+def update_image_input(state, selection):
+    print("-" * 80)
+    print("update_image_input:")
+    print(f"selection: {selection}")
+    if not selection:
+        white_image = get_start_image()
+        return (
+            white_image,
+            [white_image],
+            None,
+            None,
+            None,
+        )
+
+    image_path = os.path.join("./images", selection)
+    print(f"image_path: {image_path}")
+    if not os.path.exists(image_path):
+        raise gr.Error(f"Image not found: {image_path}")
+
+    image = Image.open(image_path)
+    image = np.array(image)
+    state["inp_image"] = image
+    return (
+        image,
+        [image],
+        None,
+        None,
+        None,
+    )
+
+
+def clear_image_input(state):
+    print("-" * 80)
+    print("clear_image_input:")
+    state["inp_image"] = None
+    return (
+        None,
+        [],
+        None,
+        None,
+        None,
+    )
+
+
+css = """
+.fft_mag > .image-container > button > div:first-child {
+    display: none;
+}
+.fft_phase > .image-container > button > div:first-child {
+    display: none;
+}
+.ifft_img > .image-container > button > div:first-child {
+    display: none;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    state = gr.State(
+        {
+            "inp_image": None,
+        },
+    )
+
+    with gr.Row():
+        with gr.Column():
+            inp_image = gr.Image(
+                value=get_start_image(),
+                label="Input Image",
+                height=512,
+                type="numpy",
+                interactive=True,
+                tool="sketch",
+                mask_opacity=1.0,
+                elem_classes=["inp_img"],
+            )
+            files = os.listdir("./images")
+            files = sorted(files)
+            inp_samples = gr.Dropdown(
+                choices=files,
+                label="Select Example Image",
+            )
+
+        with gr.Column():
+            out_gallery = gr.Gallery(
+                label="Input Gallery",
+                height=512,
+                rows=1,
+                columns=3,
+                allow_preview=True,
+                preview=False,
+                selected_index=None,
+            )
+
+            with gr.Row():
+                inp_mask_opacity = gr.Slider(
+                    label="Mask Opacity",
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.05,
+                    value=1.0,
+                )
+
+                inp_invert_mask = gr.Checkbox(
+                    label="Invert Mask",
+                    value=False,
+                )
+
+                inp_pad = gr.Checkbox(
+                    label="Pad NextPow2",
+                    value=True,
+                )
+
+    btn_fft = gr.Button("Process FFT")
+
+    out_fft_mag = gr.Image(
+        label="FFT Magnitude Spectrum",
+        height=512,
+        type="numpy",
+        interactive=True,
+        # source="canvas",
+        tool="sketch",
+        mask_opacity=1.0,
+        elem_classes=["fft_mag"],
+    )
+    out_fft_phase = gr.Image(
+        label="FFT Phase Spectrum",
+        height=512,
+        type="numpy",
+        interactive=True,
+        # source="canvas",
+        tool="sketch",
+        mask_opacity=1.0,
+        elem_classes=["fft_phase"],
+    )
+
+    btn_ifft = gr.Button("Process IFFT")
+
+    out_ifft = gr.Image(
+        label="IFFT",
+        height=512,
+        type="numpy",
+        interactive=True,
+        show_download_button=True,
+        elem_classes=["ifft_img"],
+    )
+
+    inp_image.clear(
+        clear_image_input,
+        [state],
+        [inp_samples, out_gallery, out_fft_mag, out_fft_phase, out_ifft],
+    )
+
+    # Set up event listener for the Dropdown component to update the image input
+    inp_samples.change(
+        update_image_input,
+        [state, inp_samples],
+        [inp_image, out_gallery, out_fft_mag, out_fft_phase, out_ifft],
+    )
+
+    # Set up events for fft processing
+    btn_fft.click(
+        onclick_process_fft,
+        [state, inp_image, inp_mask_opacity, inp_invert_mask, inp_pad],
+        [out_gallery, out_fft_mag, out_fft_phase],
+    )
+
+    out_fft_mag.clear(
+        onclick_process_fft,
+        [state, inp_image, inp_mask_opacity, inp_invert_mask, inp_pad],
+        [out_gallery, out_fft_mag, out_fft_phase],
+    )
+
+    out_fft_phase.clear(
+        onclick_process_fft,
+        [state, inp_image, inp_mask_opacity, inp_invert_mask, inp_pad],
+        [out_gallery, out_fft_mag, out_fft_phase],
+    )
+
+    # inp_image.edit(
+    #     get_fft_images,
+    #     [state, inp_image],
+    #     [out_gallery, out_fft_mag, out_fft_phase],
+    # )
+
+    # Set up events for ifft processing
+    btn_ifft.click(
+        onclick_process_ifft,
+        [state, out_fft_mag, out_fft_phase],
+        [out_gallery, out_ifft],
+    )
+
+    # out_fft_mag.edit(
+    #     get_ifft_image,
+    #     [state, out_fft_mag, out_fft_phase],
+    #     [out_ifft],
+    # )
+
+    # out_fft_phase.edit(
+    #     get_ifft_image,
+    #     [state, out_fft_mag, out_fft_phase],
+    #     [out_ifft],
+    # )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+numpy
+Pillow