diff --git a/src/helpers/algorithms/__pycache__/pysift.cpython-311.pyc b/src/helpers/algorithms/__pycache__/pysift.cpython-311.pyc
index 17374af..44f6a75 100644
Binary files a/src/helpers/algorithms/__pycache__/pysift.cpython-311.pyc and b/src/helpers/algorithms/__pycache__/pysift.cpython-311.pyc differ
diff --git a/src/helpers/algorithms/sift.py b/src/helpers/algorithms/sift.py
index 1243ca8..1b403de 100644
--- a/src/helpers/algorithms/sift.py
+++ b/src/helpers/algorithms/sift.py
@@ -25,7 +25,6 @@ for filename in os.listdir(os.path.join(os.getcwd(), "./res/trees/")):
     gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
     kp = sift.detect(gray, None) # deze bad 
     (kp, des)= sift.compute(gray, kp)
-
     img = cv2.drawKeypoints(
         gray,
         kp,
@@ -33,8 +32,8 @@ for filename in os.listdir(os.path.join(os.getcwd(), "./res/trees/")):
         flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
     results = np.append(results, len(kp))
     labels.append(filename.split('_', 1)[0])
-    break
-    # cv2.imshow(filename,img)
+    # break
+    cv2.imshow(filename,img)
 
 plt.bar(labels, results)
 plt.show()
diff --git a/src/helpers/algorithms/sift_v2.py b/src/helpers/algorithms/sift_v2.py
new file mode 100644
index 0000000..ce6c713
--- /dev/null
+++ b/src/helpers/algorithms/sift_v2.py
@@ -0,0 +1,69 @@
+import numpy as np
+import cv2
+import os
+import matplotlib.pyplot as plt
+import math
+
+avg_magnitudes = np.zeros(10)
+max_magnitudes = np.zeros(10)
+avg_angle = np.zeros(10)
+counts = np.zeros(10)
+i = 0
+
+for filename in os.listdir(os.path.join(os.getcwd(), "./res/trees/")):
+    ## Load an image ##
+    directory = os.path.join(os.getcwd(), "./res/trees/")
+    path = os.path.join(directory, filename)
+    img = cv2.imread(path, 0)
+
+    ## Detect Keypoints ##
+    sift = cv2.SIFT.create(enable_precise_upscale=True)
+    kp = sift.detect(img, None)
+    img = cv2.drawKeypoints(
+        img,
+        kp,
+        img, 
+        flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
+    
+    ## Average and Max size ##
+    magnitudes = [keypoint.size for keypoint in kp]
+    max_magnitudes[i] = np.amax(magnitudes)
+    avg_magnitudes[i] = np.sum(magnitudes)/len(kp)
+
+    ## Number of keypoints ##
+    counts[i] = len(kp)
+
+    ## Average angle ##
+    angle_radians = [math.radians(keypoint.angle) for keypoint in kp]
+    sum_sin = sum(math.sin(angle) for angle in angle_radians)
+    sum_cos = sum(math.cos(angle) for angle in angle_radians)
+    avg_angle_rad = math.atan2(sum_sin, sum_cos)
+    avg_angle[i] = math.degrees(avg_angle_rad) % 360
+
+    i += 1
+    # break
+    # cv2.imshow("output", img)
+    # cv2.waitKey(0)
+
+
+plt.scatter(counts, avg_magnitudes)
+plt.title("Hoeveelheid keypoints vs gemiddelde magnitude")
+plt.grid()
+plt.show()
+
+plt.scatter(counts, max_magnitudes)
+plt.title("Hoeveelheid keypoints vs maximale magnitude")
+plt.grid()
+plt.show()
+
+plt.scatter(avg_magnitudes, max_magnitudes)
+plt.title("gemiddelde magnitude vs maximale magnitude")
+plt.grid()
+plt.show()
+
+plt.scatter(counts, avg_angle)
+plt.title("Hoeveelheid keypoints vs gemiddelde hoek")
+plt.grid()
+plt.show()
+
+cv2.destroyAllWindows()