feat:

deblur/symetric_kernel.py

@@ -8,6 +8,7 @@ from PyQt5.QtWidgets import (
 from PyQt5.QtCore import Qt
 from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
 from matplotlib.figure import Figure
+import scipy.signal
 
 import os
 os.environ.pop("QT_QPA_PLATFORM_PLUGIN_PATH", None)
@@ -43,7 +44,7 @@ def generate_kernel(radius, sigma=None):
 
 
 class KernelVisualizer(QWidget):
-    def __init__(self):
+    def __init__(self, image_path=None):
         super().__init__()
         self.setWindowTitle("Gaussian Kernel Visualizer")
         self.image = None
@@ -80,16 +81,23 @@ class KernelVisualizer(QWidget):
         layout.addLayout(sliders_layout)
         layout.addWidget(QLabel("Kernel Visualization:"))
         layout.addWidget(self.kernel_canvas)
-        layout.addWidget(QLabel("Original and Blurred Image:"))
+        layout.addWidget(QLabel("Original and Deconvolved Image:"))
         layout.addWidget(self.image_canvas)
 
         self.setLayout(layout)
+        
+        if image_path:
+            self.load_image(image_path)
+        else:
             self.update_visualization()
 
-    def load_image(self):
+    def load_image(self, image_path=None):
+        if not image_path:
             fname, _ = QFileDialog.getOpenFileName(self, "Open Image", "", "Images (*.png *.jpg *.bmp *.jpeg)")
-        if fname:
+            image_path = fname
-            img = cv2.imread(fname)
+        
+        if image_path:
+            img = cv2.imread(image_path)
             if img is not None:
                 self.image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
                 self.update_visualization()
@@ -109,7 +117,21 @@ class KernelVisualizer(QWidget):
 
         if self.image is not None:
             kernel_size = 2 * radius + 1
-            blurred = cv2.GaussianBlur(self.image, (kernel_size, kernel_size), sigma)
+
+            # Apply row-by-row deconvolution
+            deconvolved_image = np.zeros_like(self.image)
+
+            # Perform row-wise deconvolution with padded kernel
+            for i in range(self.image.shape[0]):
+                padded_kernel = np.pad(kernel, ((0, self.image.shape[1] - kernel_size), (0, 0)), mode='constant')
+                deconvolved_image[i, :], _ = scipy.signal.deconvolve(self.image[i, :], padded_kernel[i, :])
+
+            # Perform column-wise deconvolution with padded kernel
+            for j in range(self.image.shape[1]):
+                padded_kernel = np.pad(kernel, ((0, self.image.shape[0] - kernel_size), (0, 0)), mode='constant')
+                deconvolved_image[:, j], _ = scipy.signal.deconvolve(self.image[:, j], padded_kernel[:, j])
+
+            deconvolved_image = np.clip(deconvolved_image, 0, 255).astype(np.uint8)  # Ensure valid range
 
             self.image_fig.clear()
             ax1 = self.image_fig.add_subplot(121)
@@ -118,8 +140,8 @@ class KernelVisualizer(QWidget):
             ax1.axis('off')
 
             ax2 = self.image_fig.add_subplot(122)
-            ax2.imshow(blurred, cmap='gray')
+            ax2.imshow(deconvolved_image, cmap='gray')
-            ax2.set_title("Blurred")
+            ax2.set_title("Deconvolved")
             ax2.axis('off')
 
             self.image_canvas.draw()
@@ -132,7 +154,12 @@ class KernelVisualizer(QWidget):
 
 
 if __name__ == "__main__":
+    image_path = None
+    if len(sys.argv) > 1:
+        image_path = sys.argv[1]  # Get image path from command-line argument
+        print(image_path)
+
     app = QApplication(sys.argv)
-    viewer = KernelVisualizer()
+    viewer = KernelVisualizer(image_path=image_path)
     viewer.show()
     sys.exit(app.exec_())