zadanie 2 w osobnym pliku

zadanie2.py

@@ -0,0 +1,94 @@
+import matplotlib.pyplot as plt
+import numpy as np
+img1 = plt.imread("wmi1.jpg")/float(2**8)
+img2 = plt.imread("wmi2.jpg")/float(2**8)
+img3 = plt.imread("wmi3.jpg")/float(2**8)
+
+#plt.imshow(img)
+#plt.show()
+
+
+def zad2(img, _diamiter, n):
+    shape = img.shape[:2]
+
+    def draw_cicle(shape,diamiter):
+        assert len(shape) == 2
+        TF = np.zeros(shape,dtype=np.bool)
+        center = np.array(TF.shape)/2.0
+
+        for iy in range(shape[0]):
+            for ix in range(shape[1]):
+                TF[iy,ix] = (iy- center[0])**2 + (ix - center[1])**2 < diamiter **2
+        return(TF)
+
+
+    TFcircleIN   = draw_cicle(shape=img.shape[:2],diamiter=_diamiter)
+    TFcircleOUT  = ~TFcircleIN
+
+
+
+    fft_img = np.zeros_like(img,dtype=complex)
+    for ichannel in range(fft_img.shape[2]):
+        fft_img[:,:,ichannel] = np.fft.fftshift(np.fft.fft2(img[:,:,ichannel]))
+
+
+
+    def filter_circle(TFcircleIN,fft_img_channel):
+        temp = np.zeros(fft_img_channel.shape[:2],dtype=complex)
+        temp[TFcircleIN] = fft_img_channel[TFcircleIN]
+        return(temp)
+
+    fft_img_filtered_IN = []
+    fft_img_filtered_OUT = []
+    ## for each channel, pass filter
+    for ichannel in range(fft_img.shape[2]):
+        fft_img_channel  = fft_img[:,:,ichannel]
+        ## circle IN
+        temp = filter_circle(TFcircleIN,fft_img_channel)
+        fft_img_filtered_IN.append(temp)
+        ## circle OUT
+        temp = filter_circle(TFcircleOUT,fft_img_channel)
+        fft_img_filtered_OUT.append(temp) 
+        
+    fft_img_filtered_IN = np.array(fft_img_filtered_IN)
+    fft_img_filtered_IN = np.transpose(fft_img_filtered_IN,(1,2,0))
+    fft_img_filtered_OUT = np.array(fft_img_filtered_OUT)
+    fft_img_filtered_OUT = np.transpose(fft_img_filtered_OUT,(1,2,0))
+
+
+
+
+
+    def inv_FFT_all_channel(fft_img):
+        img_reco = []
+        for ichannel in range(fft_img.shape[2]):
+            img_reco.append(np.fft.ifft2(np.fft.ifftshift(fft_img[:,:,ichannel])))
+        img_reco = np.array(img_reco)
+        img_reco = np.transpose(img_reco,(1,2,0))
+        return(img_reco)
+
+
+    img_reco              = inv_FFT_all_channel(fft_img)
+    img_reco_filtered_IN  = inv_FFT_all_channel(fft_img_filtered_IN)
+    img_reco_filtered_OUT = inv_FFT_all_channel(fft_img_filtered_OUT)
+
+    fig = plt.figure(figsize=(25,18))
+    ax  = fig.add_subplot(1,3,1)
+    ax.imshow(np.abs(img_reco))
+    ax.set_title("original image")
+
+    ax  = fig.add_subplot(1,3,2)
+    ax.imshow(np.abs(img_reco_filtered_IN))
+    ax.set_title("low pass filter image")
+
+
+    ax  = fig.add_subplot(1,3,3)
+    ax.imshow(np.abs(img_reco_filtered_OUT))
+    ax.set_title("high pass filtered image")
+    plt.savefig(f"zdjęcie{n}.jpg")
+    #plt.show()
+
+zad2(img1, 150, 1)
+zad2(img2, 120, 2)
+zad2(img3, 150, 3)
+