Update channel_functions.py

channel_functions.py

@@ -7,7 +7,7 @@ def individual_channel_image(img_arr, channel= 'r', ax=None):
   img_arr = img_arr[:,:,0:3]
   
   if channel in ['r','red','Red']:
-    plot_arr = img_arr[:,:,2]
+    plot_arr = img_arr[:,:,0]
     channel_name = 'Red'
     cmap = 'Reds'
   if channel in ['g','green','Green']:
@@ -15,7 +15,7 @@ def individual_channel_image(img_arr, channel= 'r', ax=None):
     channel_name = 'Green'
     cmap = 'Greens'
   if channel in ['b','blue','Blue']:
-    plot_arr = img_arr[:,:,0]
+    plot_arr = img_arr[:,:,2]
     channel_name = 'Blue'
     cmap = 'Blues'
   
@@ -48,8 +48,10 @@ def channel_distribution_plotter(img_array):
 
     img_array = img_array[:,:,:3] #Not considering the A channel, if it's a RGBA image.
 
+    fig, ax = plt.subplots(figsize=(8,8))
+    
     plt.subplot(2,2,1)
-    plt.hist(img_array[:,:,2].ravel(),bins=256,color='red');
+    plt.hist(img_array[:,:,0].ravel(),bins=256,color='red');
     plt.title("Red Channel")
 
     plt.subplot(2,2,2)
@@ -57,7 +59,7 @@ def channel_distribution_plotter(img_array):
     plt.title("Green Channel")
 
     plt.subplot(2,2,3)
-    plt.hist(img_array[:,:,1].ravel(),bins=256,color='blue');
+    plt.hist(img_array[:,:,2].ravel(),bins=256,color='blue');
     plt.title("Blue Channel")
 
     plt.subplot(2,2,4)
@@ -66,10 +68,12 @@ def channel_distribution_plotter(img_array):
 
     plt.suptitle("Pixel values distribution in each channel\nx-axis: pixel values, y-axis: number of pixels")
     plt.tight_layout()
-
+    
     plt.show()
-
-
+    fig.canvas.draw()
+    image_array = np.array(fig.canvas.renderer.buffer_rgba())
+    return image_array
+     
 
 
 def which_channel_dominates(img_arr, original_image_plot = 'yes', original_image_opacity = 0.3, channel_opacity = 0.7):