Canny F U N C

src/suite.py

@@ -41,7 +41,8 @@ class MainApp:
 
         # Keep track of images in dataset
         self.img_current = 0
-        self.img_old = -1
+        self.img_name = ""
+        self.img_old = -1 ## minus 1 to enforce full update on start
         self.img_max = 0
 
         # Plots
@@ -129,6 +130,9 @@ class MainApp:
             print("Nothing to export!")
             
     def apply_all(self, event=None):
+        '''
+            Export given preprocess id for every image in the dataset folder
+        '''
         img_id = self.export_id.get()
         img_current = copy.deepcopy(self.img_current)
         
@@ -167,6 +171,7 @@ class MainApp:
         
         self.meta.config(state=NORMAL)
         self.meta.delete(1.0, END)
+        self.meta.insert(END, f"{self.img_name[1]}\n")        
         
         # Draw all output images
         for idx, data in enumerate(self.output[0]):
@@ -233,7 +238,14 @@ class MainApp:
                 # print(f"Result at thres {th1}, {th2}; \tIndex {y_ind}, {x_ind} \t= {w_res}")
                 # print(results[y_ind])
                 
-        self.axs[column, row].title.set_text(F"Mean: {np.matrix(results).mean()}")
+                
+        func = np.diag(results)
+        self.axs[column, row-1].clear()
+        self.axs[column, row-1].title.set_text("Canny F U N C")
+        self.axs[column, row-1].plot(func)
+        self.axs[column, row-1].plot(np.diff(func))
+        
+        self.axs[column, row].title.set_text(F"Mean: {np.matrix(results).mean()}\nStd: {np.matrix(results).std()}")
         self.axs[column, row].imshow(results)
         self.axs[column, row].xaxis.set_major_formatter(lambda x, pos: str(x*canny_step))
         self.axs[column, row].yaxis.set_major_formatter(lambda x, pos: str(x*canny_step))
@@ -241,7 +253,7 @@ class MainApp:
     def writeStats(self, img, labels, column, row):
         mean, std = imgStats(img)
         self.axs[column, row].title.set_text(
-            "mean: %c:%d %c:%d %c:%d \n std: %c:%d %c:%d %c:%d"
+            "Mean: %c:%d %c:%d %c:%d \nStd: %c:%d %c:%d %c:%d"
             %(labels[0], mean[0], labels[1], mean[1], labels[2], mean[2], 
                 labels[0], std[0], labels[1], std[1], labels[2], std[2]))
     
@@ -262,10 +274,11 @@ class MainApp:
         if path != None and path != "":
             # Get all images at current path
             images = []
-            for file in glob.glob(path + "/*.png"):
+            for file in glob.glob(path + "/*.jpg"):
                 images.append(file)
                 
             self.img_max = len(images)
+            self.img_name = os.path.split(images[self.img_current])
                 
             # Get all user vars
             ct1 = self.canny_thr1.get()
@@ -319,7 +332,6 @@ class MainApp:
             # Canny edge
             img_canny = cv2.Canny(image=img_blur,threshold1=ct1,threshold2=ct2)
             self.add_output(img_canny, "Canny_edge")
-            self.writeStats(img, ('B', 'G', 'R'), 0, 0)
 
             # BGR
             self.add_output(img[:, :, 0], "BGR_B")
@@ -328,6 +340,7 @@ class MainApp:
 
             if img is not None:
                 self.drawHist(img, ('B', 'G', 'R'), 0, 0)
+                self.writeStats(img, ('B', 'G', 'R'), 0, 0)
             
             # HSV
             img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)