回答編集履歴
2
d
test
CHANGED
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@@ -50,6 +50,10 @@
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contours = list(filter(lambda x: cv2.contourArea(x) > 100, contours))
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dists = []
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for cnt in contours:
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x, y, w, h = cv2.boundingRect(target_cnt)
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cropped = img[y:y + h, x:x + w]
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cropped = img[y : y + h, x : x + w]
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1
d
test
CHANGED
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@@ -14,27 +14,11 @@
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import numpy as np
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#from IPython.display import Image, display
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#def imshow(img):
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# img = cv2.imencode(".png", img)[1]
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# display(Image(img))
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# 画像を読み込む。
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img = cv2.imread("sample.jpg")
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#imshow(img)
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@@ -46,8 +30,6 @@
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retval, binary = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)
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#imshow(binary)
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# 輪郭の検出
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@@ -57,12 +39,6 @@
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binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
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)
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cv2.drawContours(img, contours, -1, color=(0, 255, 0))
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#imshow(img)
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# 中心から最も距離が近い輪郭
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# 中心から最も距離が近い輪郭を取得する。
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idx = np.argmin(dists)
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target_cnt = contours[idx]
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cv2.drawContours(img, contours, idx, color=(0, 0, 255), thickness=5)
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#
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# その輪郭の外接矩形を取得する。
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x, y, w, h = cv2.boundingRect(target_cnt)
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cropped = img[y:y + h, x:x + w]
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cv2.imwrite("result.png", cropped)
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```
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入力画像
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↓
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切り抜き画像
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