質問編集履歴
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追記
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File without changes
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@@ -5,24 +5,48 @@
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5
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を使うと、クラスタリングで色を取得したあとになぜかRGBAに変換されてしまうので、
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RGB値を直接LAB値に変換するにはどのようにすればいいのでしょうか？
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#追記
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9
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以下のk-meansでlabの値を求めたのですが、LABは０〜１００の間の値しか取らないのに、100を超えてしまいます。これはlABではないのでしょうか？
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```python
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-
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def load_image(image_file):
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# cv2 load images as BGR, convert it to LAB
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image_bgr = cv2.imread(image_file)
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-
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image_lab = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2LAB)
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if image_Lab is not None:
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-
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image_lab = cv2.resize(image_lab, (150, 150))
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return
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return image_lab
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def centroid_histogram(clt):
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21
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numLabels = np.arange(0, len(np.unique(clt.labels_)) + 1)
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(hist, _) = np.histogram(clt.labels_, bins = numLabels)
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-
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hist = hist.astype("float")
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-
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hist /= hist.sum()
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-
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return hist
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def plot_colors(hist, centroids):
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bar = np.zeros((50, 300, 3), dtype = "uint8")
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startX = 0
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for (percent, color) in zip(hist, centroids):
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endX = startX + (percent * 300)
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-
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cv2.rectangle(bar, (int(startX), 0), (int(endX), 50),
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color.astype("uint8").tolist(), -1)
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startX = endX
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-
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return bar
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image = image.reshape(-1,3)
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clt = KMeans(n_clusters =3)
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clt.fit(image)
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hist = centroid_histogram(clt)
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-
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bar = plot_colors(hist, clt.cluster_centers_)
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#
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# show our color bart
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plt.figure()
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plt.axis("off")
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plt.imshow(bar)
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plt.show()
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48
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resized = cv2.resize(bar, (bar.shape[0], bar.shape[1]))
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49
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ch_imgs = cv2.split(resized)
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ch_imgs
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>>>136,144, 145
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```
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