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""" |
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Utility functions for image processing GUI. |
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""" |
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from PyQt5.QtGui import QPixmap |
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from PyQt5.QtCore import Qt |
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from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas |
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from matplotlib.figure import Figure |
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from PIL import Image |
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import numpy as np |
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def qpixmap_from_path(p: str, max_size=(480, 360)) -> QPixmap: |
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pix = QPixmap(p) |
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if pix.isNull(): |
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return QPixmap() |
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w, h = max_size |
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return pix.scaled(w, h, Qt.KeepAspectRatio, Qt.SmoothTransformation) |
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def make_canvas(width=4, height=3, dpi=100): |
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fig = Figure(figsize=(width, height), dpi=dpi) |
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canvas = FigureCanvas(fig) |
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ax = fig.add_subplot(111) |
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fig.tight_layout() |
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return canvas, ax |
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def compute_gray_array(path): |
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img = Image.open(path).convert('RGB') |
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arr = np.array(img) |
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gray = (0.299 * arr[:, :, 0] + 0.587 * arr[:, :, 1] + 0.114 * arr[:, :, 2]).astype(np.float32) |
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return gray |
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def compute_fft_magnitude(gray_arr, eps=1e-8): |
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f = np.fft.fft2(gray_arr) |
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fshift = np.fft.fftshift(f) |
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mag = np.abs(fshift) |
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mag_log = np.log1p(mag) |
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return mag, mag_log |
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def radial_profile(mag, center=None, nbins=100): |
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h, w = mag.shape |
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if center is None: |
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center = (int(h / 2), int(w / 2)) |
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y, x = np.indices((h, w)) |
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r = np.sqrt((x - center[1]) ** 2 + (y - center[0]) ** 2) |
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r_flat = r.ravel() |
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mag_flat = mag.ravel() |
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max_r = np.max(r_flat) |
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if max_r <= 0: |
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return np.linspace(0, 1, nbins), np.zeros(nbins) |
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bins = np.linspace(0, max_r, nbins + 1) |
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inds = np.digitize(r_flat, bins) - 1 |
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radial_mean = np.zeros(nbins) |
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for i in range(nbins): |
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sel = inds == i |
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if np.any(sel): |
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radial_mean[i] = mag_flat[sel].mean() |
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else: |
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radial_mean[i] = 0.0 |
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centers = 0.5 * (bins[:-1] + bins[1:]) / max_r |
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return centers, radial_mean |
