Sift v3 improvements
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@ -3,15 +3,19 @@ import cv2
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import os
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import matplotlib.pyplot as plt
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DATASET_PATH = "C:\\Users\\tomse\\Documents\\Dataset\\"
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DATASET_PATH = "C:\\Users\\tomse\\Downloads\\Dataset\\"
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DATASET_FOLDERS_LEN = len(os.listdir(DATASET_PATH))
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EARLY_BREAK = 3
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EARLY_BREAK = 0
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SCALE = 1
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# Plataan, Berk, Accasia
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sift = cv2.SIFT.create(enable_precise_upscale=True)
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## Create 2D lists ##
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max_magnitudes = [[] for x in range(DATASET_FOLDERS_LEN)]
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avg_magnitudes = [[] for x in range(DATASET_FOLDERS_LEN)]
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tot_magnitudes = [[] for x in range(DATASET_FOLDERS_LEN)]
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counts = [[] for x in range(DATASET_FOLDERS_LEN)]
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## Create other variables ##
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@ -19,6 +23,9 @@ labels = ['' for x in range(DATASET_FOLDERS_LEN)]
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i = 0
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for folder in os.listdir(DATASET_PATH):
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if not folder.endswith("_out"):
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continue
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if EARLY_BREAK:
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print("Step %d/%d processing %s:"%(i+1, EARLY_BREAK, folder))
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else:
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@ -28,18 +35,27 @@ for folder in os.listdir(DATASET_PATH):
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## Load an image ##
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path = DATASET_PATH + folder + "\\" + file
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full_image = cv2.imread(path, 0)
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image = cv2.resize(full_image, (0, 0), fx=0.25, fy=0.25)
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image = cv2.resize(full_image, (0, 0), fx=SCALE, fy=SCALE)
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## Detect keypoints ##
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kp = sift.detect(image, None)
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image = cv2.drawKeypoints(
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image,
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kp,
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image,
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flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
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## Average and Max size ##
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magnitudes = [keypoint.size for keypoint in kp]
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tot_magnitudes[i].append(np.sum(magnitudes))
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max_magnitudes[i].append(np.amax(magnitudes))
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avg_magnitudes[i].append(np.sum(magnitudes)/len(kp))
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## Number of keypoints ##
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counts[i].append(len(kp))
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# cv2.imshow("Opencv tech", image)
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# cv2.waitKey(0)
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## Store labels ##
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labels[i] = folder
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@ -54,8 +70,21 @@ print("Done!")
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## Plots ##
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fig, ax = plt.subplots()
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for i in range(DATASET_FOLDERS_LEN):
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ax.scatter(avg_magnitudes[i], max_magnitudes[i],label=labels[i], alpha=0.7)
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ax.legend()
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# for i in range(DATASET_FOLDERS_LEN):
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# ax.scatter(tot_magnitudes[i], max_magnitudes[i],label=labels[i], alpha=0.7)
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# ax.scatter(avg_magnitudes[0], max_magnitudes[0], label=labels[0], alpha=0.7)
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# ax.scatter(avg_magnitudes[7], max_magnitudes[7], label=labels[7], alpha=0.7)
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# ax.set_xlabel("Gemiddelde magnitude")
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# ax.set_ylabel("Maximale magnitude")
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# ax.legend()
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# ax.grid(True)
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# plt.show()
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ax.scatter(tot_magnitudes[2], max_magnitudes[2], label='Berk', alpha=0.7)
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ax.scatter(tot_magnitudes[3], max_magnitudes[3], label='Els', alpha=0.7)
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ax.scatter(tot_magnitudes[7], max_magnitudes[7], label='Plataan', alpha=0.7)
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ax.set_xlabel("Total magnitude")
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ax.set_ylabel("Maximal magnitude")
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ax.legend()
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ax.grid(True)
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plt.show()
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plt.show()
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