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#!/usr/bin/env python3
"""
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 |