added validation statistics

.gitignore

@@ -8,4 +8,5 @@ training_data/training_data_*/
 training_data/*.vec
 training_data/backgrounds.txt
 training_data/negatives
-training_data/opencv
+training_data/opencv
+validation/cascade*

validation/compare_to_gt.py

@@ -0,0 +1,97 @@
+import argparse
+import os
+
+def dir_path(string):
+    if os.path.exists(string):
+        return string
+    else:
+        raise NotADirectoryError(string)
+
+def init_argparse() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        prog="FaceDetection",
+        usage="%(prog)s [OPTION]",
+        description="Run face localization"
+    )
+    parser.add_argument(
+        "ground_truth", type=dir_path, help="ground truth file"
+    )
+    parser.add_argument(
+        "test_file", type=dir_path, help="file to compare to the ground truth"
+    )
+    parser.add_argument(
+        "out_file", help="the file to write the output to"
+    )
+    return parser
+
+multiplication_factor = 0.05
+def get_adjustment_amount(imgSize, x1, y1, x2, y2):
+
+    # find the difference between the left gap and the right gap, divide it by two, and multiply it by the speed scale
+    horizontal_adjustment = multiplication_factor * (x1 - (imgSize[0] - x2)) / 2
+    vertical_adjustment = multiplication_factor * (y1 - (imgSize[0] - y2)) / 2
+
+    return [horizontal_adjustment, vertical_adjustment]
+
+parser = init_argparse()
+args = parser.parse_args()
+
+class FrameBox:
+    frame_number: int 
+    top_left: tuple 
+    bottom_right: tuple
+
+    def __init__(self, frame_number, x1, y1, x2, y2):
+        self.frame_number = frame_number
+        self.top_left = (x1, y1)
+        self.bottom_right = (x2, y2)
+
+ground_truth = []
+with open(args.ground_truth, 'r') as gt_file:
+    lines = gt_file.readlines()
+    for line in lines:
+        items = line.split(",")
+        ground_truth.append(FrameBox(int(items[0].strip()), int(items[1].strip()), int(items[2].strip()), int(items[3].strip()), int(items[4].strip())))
+
+test_results = []
+with open(args.test_file, 'r') as test_file:
+    lines = test_file.readlines()
+    for line in lines:
+        items = line.split(",")
+        test_results.append(FrameBox(int(items[0].strip()), int(items[1].strip()), int(items[2].strip()), int(items[3].strip()), int(items[4].strip())))
+
+test_fb: FrameBox
+gt_frame: FrameBox
+last_frame_num = 0
+average_sum = 0
+average_count = 0
+print("length of test file: " + str(len(test_results)))
+for test_fb in test_results:
+    # make
+    def bring_up_gt():
+        if test_fb.frame_number > ground_truth[0].frame_number:
+            ground_truth.pop(0)
+            bring_up_gt()
+
+    bring_up_gt()
+
+    assert(ground_truth[0].frame_number == test_fb.frame_number)
+    gt_frame = ground_truth[0]
+
+    gt_adjustment = get_adjustment_amount((1920, 1000), gt_frame.top_left[0], gt_frame.top_left[1], gt_frame.bottom_right[0], gt_frame.bottom_right[1])
+    test_adjustment = get_adjustment_amount((1920, 1000), test_fb.top_left[0], test_fb.top_left[1], test_fb.bottom_right[0], test_fb.bottom_right[1])
+
+    if last_frame_num != test_fb.frame_number and average_count != 0:
+        with open(args.out_file, 'a') as out_file:
+            out_file.write(f"{average_sum},\n")
+        average_sum = 0
+        average_count = 0
+
+    average_count += 1
+    # get the average 
+    average_sum += abs(( (gt_adjustment[0] - test_adjustment[0]) + (gt_adjustment[1] - test_adjustment[1]) ) / 2)
+    
+    last_frame_num = test_fb.frame_number
+    
+
+    

validation/ground_truth.txt

@@ -1,4 +1,3 @@
-frame_number, top_left_x, top_left_y, bottom_right_x, bottom_right_y
 0, 856, 189, 1202, 623
 1, 856, 189, 1202, 623
 2, 857, 189, 1203, 623