Merge branch 'main' of https://arnweb.nl/gitea/arne/EV5_Beeldherk_Bomen

src/helpers/algorithms/colourspace.py

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+import cv2
+import matplotlib.pyplot as plt
+
+DATASET_PATH = "C:\\Users\\tomse\\Documents\\Dataset\\"
+
+full_img = cv2.imread(DATASET_PATH + "alder\\1.jpg", 1)
+bgr_img = cv2.resize(full_img, (0, 0), fx=0.2, fy=0.2)
+hsv_img = cv2.cvtColor(bgr_img, cv2.COLOR_BGR2HSV)
+
+cv2.imshow('BGR',bgr_img)
+cv2.imshow('HSV',hsv_img)
+cv2.imshow('HSV - H',hsv_img[:, :, 0])
+cv2.imshow('HSV - S',hsv_img[:, :, 1])
+cv2.imshow('HSV - V',hsv_img[:, :, 2])
+
+
+hist = cv2.calcHist([hsv_img], [0], None, [256], [0,256])
+plt.plot(hist, label='H')
+hist = cv2.calcHist([hsv_img], [1], None, [256], [0,256])
+plt.plot(hist, label='S')
+hist = cv2.calcHist([hsv_img], [2], None, [256], [0,256])
+plt.plot(hist, label='V')
+plt.grid()
+plt.legend()
+plt.show()
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()

src/helpers/algorithms/sift_v3.py

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+import numpy as np
+import cv2
+import os
+import matplotlib.pyplot as plt
+
+DATASET_PATH = "C:\\Users\\tomse\\Documents\\Dataset\\"
+DATASET_FOLDERS_LEN = len(os.listdir(DATASET_PATH))
+EARLY_BREAK = 3
+
+sift = cv2.SIFT.create(enable_precise_upscale=True)
+
+## Create 2D lists ##
+max_magnitudes = [[] for x in range(DATASET_FOLDERS_LEN)]
+avg_magnitudes = [[] for x in range(DATASET_FOLDERS_LEN)]
+counts = [[] for x in range(DATASET_FOLDERS_LEN)]
+
+## Create other variables ##
+labels = ['' for x in range(DATASET_FOLDERS_LEN)]
+i = 0
+
+for folder in os.listdir(DATASET_PATH):
+    if EARLY_BREAK:
+        print("Step %d/%d processing %s:"%(i+1, EARLY_BREAK, folder))
+    else:
+        print("Step %d/%d processing %s:"%(i+1, DATASET_FOLDERS_LEN, folder))
+
+    for file in os.listdir(DATASET_PATH + folder):
+        ## Load an image ##
+        path = DATASET_PATH + folder + "\\" + file
+        full_image = cv2.imread(path, 0)
+        image = cv2.resize(full_image, (0, 0), fx=0.25, fy=0.25)
+
+        ## Detect keypoints ## 
+        kp = sift.detect(image, None)
+
+        ## Average and Max size ##
+        magnitudes = [keypoint.size for keypoint in kp]
+        max_magnitudes[i].append(np.amax(magnitudes))
+        avg_magnitudes[i].append(np.sum(magnitudes)/len(kp))
+        
+        ## Number of keypoints ##
+        counts[i].append(len(kp))
+    
+    ## Store labels ##
+    labels[i] = folder
+
+    ## Increment folder ##    
+    i += 1
+
+    if(i == EARLY_BREAK):
+        break
+
+print("Done!")
+
+## Plots ##
+fig, ax = plt.subplots()
+for i in range(DATASET_FOLDERS_LEN):
+    ax.scatter(avg_magnitudes[i], max_magnitudes[i],label=labels[i], alpha=0.7)
+ax.legend()
+ax.grid(True)
+plt.show()