Changed Dataset

Author: ZikraAknes

README.md

@@ -1,38 +1,40 @@
 import os
 
-folder_path = "training_dataset/masks/road"
+land_path = "training_dataset/masks/land"
+road_path = "training_dataset/masks/road"
 img_path = "training_dataset/images"
 
-i = 0
-x = 0
-y = 0
-
-paths = []
-all_files = []
-same_files = []
-
-for dir_path, dir_names, file_names in os.walk(folder_path):
-    if x == 0:
-        all_files = file_names
-        for dir_path_img, dir_names_img, file_names_img in os.walk(img_path):
-            if y == 0:
-                for files in file_names:
-                    for files_img in file_names_img:
-                        if files_img == files:
-                            i+=1
-                            same_files.append(files)
-                            break
-            y+=1
-    x+=1    
-    
-                    
-
-print(len(same_files))
-print(len(all_files))
-
-temp3 = [x for x in all_files if x not in same_files]
-
-print(len(temp3))
-
-for path in temp3:
-    os.remove(folder_path+"/"+path)
+def delete_files(folder_path):
+    i = 0
+    x = 0
+    y = 0
+
+    paths = []
+    all_files = []
+    same_files = []
+
+    for dir_path, dir_names, file_names in os.walk(folder_path):
+        if x == 0:
+            all_files = file_names
+            for dir_path_img, dir_names_img, file_names_img in os.walk(img_path):
+                if y == 0:
+                    for files in file_names:
+                        for files_img in file_names_img:
+                            if files_img == files:
+                                i+=1
+                                same_files.append(files)
+                                break
+                y+=1
+        x+=1    
+
+    temp3 = [x for x in all_files if x not in same_files]
+
+    print("Total Files: ",len(all_files))
+    print("Same Files",len(same_files))
+    print("Deleted Files: ",len(temp3))
+
+    for path in temp3:
+        os.remove(folder_path+"/"+path)
+
+delete_files(road_path)
+delete_files(land_path)

delete_dataset.py

@@ -7,7 +7,7 @@
 import segmentation_models as sm
 
 # Used input
-input_num = 2
+input_num = 1
 
 # Training parameter
 test_size = 0.2
@@ -262,7 +262,7 @@ def fill_area(img):
 
 model = create_model()
 
-model_path = os.path.join("model/model.h5")
+model_path = os.path.join("model/model_1.h5")
 model.load_weights(model_path)
 
 tf.debugging.set_log_device_placement(True)
@@ -280,7 +280,7 @@ def fill_area(img):
 
 # Create Trackbars
 cv2.namedWindow("Trackbars")
-cv2.createTrackbar("Treshold", "Trackbars", 1, 100, nothing)
+cv2.createTrackbar("Treshold", "Trackbars", 10, 100, nothing)
 cv2.createTrackbar("Lower Limit", "Trackbars", 25, 179, nothing)
 cv2.createTrackbar("Upper Limit", "Trackbars", 87, 179, nothing)
 cv2.createTrackbar("Area Tolerance", "Trackbars", 50000, 90000, nothing)
@@ -301,7 +301,7 @@ def fill_area(img):
         # Predict mask
         pred = model.predict(np.expand_dims(frame, 0))
 
-        range_tresh = cv2.getTrackbarPos("Treshold", "Trackbars") / 1000
+        range_tresh = cv2.getTrackbarPos("Treshold", "Trackbars") / 10000
 
         # Process mask
         mask = pred.squeeze()