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

src/experiments/algorithms/sift_v3.py

@@ -3,15 +3,19 @@ import cv2
 import os
 import matplotlib.pyplot as plt
 
-DATASET_PATH = "C:\\Users\\tomse\\Documents\\Dataset\\"
+DATASET_PATH = "C:\\Users\\tomse\\Downloads\\Dataset\\"
 DATASET_FOLDERS_LEN = len(os.listdir(DATASET_PATH))
-EARLY_BREAK = 3
+EARLY_BREAK = 0
+SCALE = 1
+
+# Plataan, Berk, Accasia
 
 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)]
+tot_magnitudes = [[] for x in range(DATASET_FOLDERS_LEN)]
 counts = [[] for x in range(DATASET_FOLDERS_LEN)]
 
 ## Create other variables ##
@@ -19,6 +23,9 @@ labels = ['' for x in range(DATASET_FOLDERS_LEN)]
 i = 0
 
 for folder in os.listdir(DATASET_PATH):
+    if not folder.endswith("_out"):
+        continue
+
     if EARLY_BREAK:
         print("Step %d/%d processing %s:"%(i+1, EARLY_BREAK, folder))
     else:
@@ -28,18 +35,27 @@ for folder in os.listdir(DATASET_PATH):
         ## 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)
+        image = cv2.resize(full_image, (0, 0), fx=SCALE, fy=SCALE)
 
         ## Detect keypoints ## 
         kp = sift.detect(image, None)
+        image = cv2.drawKeypoints(
+            image,
+            kp,
+            image, 
+            flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
 
         ## Average and Max size ##
         magnitudes = [keypoint.size for keypoint in kp]
+        tot_magnitudes[i].append(np.sum(magnitudes))
         max_magnitudes[i].append(np.amax(magnitudes))
         avg_magnitudes[i].append(np.sum(magnitudes)/len(kp))
         
         ## Number of keypoints ##
         counts[i].append(len(kp))
+
+        # cv2.imshow("Opencv tech", image)
+        # cv2.waitKey(0)
     
     ## Store labels ##
     labels[i] = folder
@@ -54,8 +70,21 @@ print("Done!")
 
 ## Plots ##
 fig, ax = plt.subplots()
-for i in range(DATASET_FOLDERS_LEN):
+# for i in range(DATASET_FOLDERS_LEN):
-    ax.scatter(avg_magnitudes[i], max_magnitudes[i],label=labels[i], alpha=0.7)
+#     ax.scatter(tot_magnitudes[i], max_magnitudes[i],label=labels[i], alpha=0.7)
-ax.legend()
+# ax.scatter(avg_magnitudes[0], max_magnitudes[0], label=labels[0], alpha=0.7)
+# ax.scatter(avg_magnitudes[7], max_magnitudes[7], label=labels[7], alpha=0.7)
+# ax.set_xlabel("Gemiddelde magnitude")
+# ax.set_ylabel("Maximale magnitude")
+# ax.legend() 
+# ax.grid(True)
+# plt.show()
+
+ax.scatter(tot_magnitudes[2], max_magnitudes[2], label='Berk', alpha=0.7)
+ax.scatter(tot_magnitudes[3], max_magnitudes[3], label='Els', alpha=0.7)
+ax.scatter(tot_magnitudes[7], max_magnitudes[7], label='Plataan', alpha=0.7)
+ax.set_xlabel("Total magnitude")
+ax.set_ylabel("Maximal magnitude")
+ax.legend() 
 ax.grid(True)
-plt.show()
+plt.show()

src/experiments/template_extraction/script.py

@@ -110,6 +110,8 @@ for folder in os.listdir(input_directory):
             if VERBOSE:
                 print("Created folder: " + out_folder)
             os.mkdir(out_folder)
+        else:
+            continue
 
     for file in os.listdir(os.path.join(input_directory, folder)):
         ## Laad plaatjes in kleur ##
@@ -139,6 +141,9 @@ for folder in os.listdir(input_directory):
             corners, 
             ids)
         
+        if VERBOSE:
+            print("IDs detected:\n", ids)
+
         if ids is None:
             print("Skipping: ", filename)
             print("=============================================")