added some feature detection algorithms

src/helpers/algorithms/orb.py

@@ -0,0 +1,36 @@
+import cv2
+import os
+import matplotlib.pyplot as plt
+import numpy as np
+
+path = os.path.join(os.getcwd(), './res/trees/accasia_sq1_original.png')
+
+orb = cv2.ORB.create(nfeatures=int(10e6))
+
+results = np.zeros(0)
+labels = []
+for filename in os.listdir(os.path.join(os.getcwd(), "./res/trees/")):
+    directory = os.path.join(os.getcwd(), "./res/trees/")
+    path = os.path.join(directory, filename)
+    img = cv2.imread(path ,1)
+    gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+
+    kp = orb.detect(gray, None)
+    kp, des = orb.compute(img, kp)
+
+    gray = cv2.drawKeypoints(
+        gray, 
+        kp, 
+        None, 
+        #flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS
+        )
+    results = np.append(results, len(kp))
+    labels.append(filename.split('_', 1)[0])
+    print(len(des))
+    cv2.imshow(path, gray)
+
+plt.bar(labels, results)
+plt.show()
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()

src/helpers/algorithms/sift.py

@@ -0,0 +1,35 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import cv2
+import os
+
+# references:
+# https://docs.opencv.org/4.x/da/df5/tutorial_py_sift_intro.html
+
+
+path = os.path.join(os.getcwd(), './res/trees/accasia_sq1_original.png')
+
+sift = cv2.SIFT.create(enable_precise_upscale=True)
+
+results = np.zeros(0)
+labels = []
+for filename in os.listdir(os.path.join(os.getcwd(), "./res/trees/")):
+    directory = os.path.join(os.getcwd(), "./res/trees/")
+    path = os.path.join(directory, filename)
+    img = cv2.imread(path ,1)
+    gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
+    kp = sift.detect(gray, None)
+    img = cv2.drawKeypoints(
+        gray,
+        kp,
+        img, 
+        flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
+    results = np.append(results, len(kp))
+    labels.append(filename.split('_', 1)[0])
+    cv2.imshow(filename,img)
+
+plt.bar(labels, results)
+plt.show()
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()