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