質問編集履歴
6
コード修正
test
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```
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修正後
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```python
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import cv2
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import math
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import numpy as np
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img_src = cv2.imread("test.jpg")
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gauss = cv2.GaussianBlur(img_src, (11, 11), 0)
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gray = cv2.cvtColor(gauss, cv2.COLOR_BGR2GRAY)
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ret,th1 = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)
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edges = cv2.Canny(th1, 50, 150)
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img, contours, hierarchy = cv2.findContours(th1, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_L1)
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for i in range(0, len(contours)):
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#for cnt in contours:
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cnt = contours[i]
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area = cv2.contourArea(cnt)
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#print(area)
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if 500 < area < 5000:
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rect = cv2.minAreaRect(cnt)
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box = cv2.boxPoints(rect)
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(cx, cy), (width, height), angle = rect
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diag = np.linalg.norm([width, height])
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#print(width, height, diag)
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# 161.91236877441406 16.144147872924805 162.715237986
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#
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A = width
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B = height
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C = diag
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if A < B:
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min = A
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else:
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min = B
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if C < min:
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min = C
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print("min", min)
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if 5 < min < 25:
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#
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cv2.drawContours(img_src, [box.astype(int)], -1, (0, 255, 0), 2)
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def within(line, rect):
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p1, p2 = tuple(line[:2]), tuple(line[2:])
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#print("p1",p1)
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#print("p2",p2)
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#print("line",line)
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return cv2.pointPolygonTest(box, p1, False) >= 0 and \
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cv2.pointPolygonTest(box, p2, False) >= 0
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LSD = cv2.createLineSegmentDetector()
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lines, width, prec, nfa = LSD.detect(edges)
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if lines is not None:
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lines = np.squeeze(lines,axis=1)
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#if lines.dims == 1:
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# lines = np.expand_dims(lines, axis=0)
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for line in lines:
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p1, p2 = tuple(line[:2]), tuple(line[2:])
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print("line",line)
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if within(line, rect):
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cv2.line(img_src, p1, p2, (0, 0, 255), 2)
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#else:
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# cv2.line(img_src, p1, p2, (255, 0, 0), 2)
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cv2.imshow('src', img_src)
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cv2.waitKey()
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cv2.destroyAllWindows()
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```
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5
コードの追加
test
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File without changes
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test
CHANGED
@@ -207,3 +207,185 @@
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```
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コードが見づらくて申し訳ありません
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```python
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import cv2
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import math
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import numpy as np
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img_src = cv2.imread("./haku/sample/image1.ppm")
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gauss = cv2.GaussianBlur(img_src,(11,11),0)#9,9
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gray = cv2.cvtColor(gauss,cv2.COLOR_BGR2GRAY)
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ret,th1 = cv2.threshold(gray,200,255,cv2.THRESH_BINARY)
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edges = cv2.Canny(th1,50,150)#(100,150)
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img, contours, hierarchy = cv2.findContours(th1, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_L1)
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if len(contours) > 0:
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for i in range(0, len(contours)):
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cnt = contours[i]
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M = cv2.moments(cnt)
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#print(M)
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area = cv2.contourArea(cnt)
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print(area)
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if 500 < area < 5000:
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rect = cv2.minAreaRect(contours[i])
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box = cv2.boxPoints(rect)
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box = np.int0(box)
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x1,x2,x3,x4 = np.int0(box)
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a = np.array(x1)
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b = np.array(x2)
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c = np.array(x3)
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d = np.array(x4)
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A = np.linalg.norm(a-b)
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277
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B = np.linalg.norm(a-c)
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C = np.linalg.norm(a-d)
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281
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282
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print("頂点",x1,x2,x3,x4)
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#print("abcd", a,b,c,d)
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287
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#print("Aの長さ", A)
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289
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#print("Bの長さ",B)
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#print("Cの長さ",C)
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293
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294
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295
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if A < B:
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min = A
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else:
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300
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301
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min = B
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302
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303
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+
if C < min:
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304
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+
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305
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min = C
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307
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+
print("最小",min)
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308
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|
309
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+
if 5 < min < 25:
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310
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+
|
311
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+
im = cv2.drawContours(img_src,[box],0,(0,255,0),2)
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312
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+
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313
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314
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315
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def within(line, rect):
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318
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319
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"""line が rect に含まれるかどうか
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320
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321
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"""
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322
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+
|
323
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+
p1, p2 = tuple(line[:2]), tuple(line[2:])
|
324
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+
|
325
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+
# 線の始点と終点が長方形内に含まれるかどうか
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326
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+
|
327
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+
return cv2.pointPolygonTest(box, p1, False) >= 0 and \
|
328
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+
|
329
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+
cv2.pointPolygonTest(box, p2, False) >= 0
|
330
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+
|
331
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+
|
332
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+
|
333
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+
LSD = cv2.createLineSegmentDetector()
|
334
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+
|
335
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+
lines, width, prec, nfa = LSD.detect(edges)
|
336
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+
|
337
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+
print(lines.shape)
|
338
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+
|
339
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+
lines = np.squeeze(lines)
|
340
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+
|
341
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+
|
342
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+
|
343
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+
if lines is not None:
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344
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+
|
345
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+
for i in range(len(lines)):
|
346
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+
|
347
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+
|
348
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+
|
349
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+
#for x1,y1,x2,y2 in lines[i] :
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350
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+
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351
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+
# cv2.line(img_src,(x1,y1),(x2,y2),(0,0,255),2)
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352
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+
|
353
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+
# X1 = (x1, y1)
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354
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+
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355
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+
# X2 = (x2, y2)
|
356
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+
|
357
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+
# print("X1", X1)
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358
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+
|
359
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+
#print("X2", X2)
|
360
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+
|
361
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+
for line in lines:
|
362
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+
|
363
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+
p1, p2 = tuple(lines[:2]), tuple(line[2:])
|
364
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+
|
365
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+
if within(line, rect):
|
366
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+
|
367
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+
# 長方形に含まれる場合は赤色で描画
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368
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+
|
369
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+
cv2.line(img_src, p1, p2, (0, 0, 255), 2)
|
370
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+
|
371
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+
else:
|
372
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+
|
373
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+
# 長方形に含まれない場合は赤色で描画
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374
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+
|
375
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+
cv2.line(img_src, p1, p2, (255, 0, 0), 2)
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376
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+
|
377
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+
|
378
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+
|
379
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+
|
380
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+
|
381
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+
#cv2.imwrite("teratail.jpg", img_src)
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382
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+
|
383
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+
cv2.imshow('src', img_src)
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384
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+
|
385
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+
cv2.waitKey()
|
386
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+
|
387
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+
cv2.destroyAllWindows()
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388
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+
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389
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+
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390
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391
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+
```
|
4
コードの追記
test
CHANGED
File without changes
|
test
CHANGED
@@ -122,7 +122,45 @@
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122
122
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123
123
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d = np.array(x4)
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124
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|
125
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+
|
126
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+
|
127
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+
A = np.linalg.norm(a-b)
|
128
|
+
|
129
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+
B = np.linalg.norm(a-c)
|
130
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+
|
131
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+
C = np.linalg.norm(a-d)
|
132
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+
|
133
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+
|
134
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+
|
135
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+
print("頂点",x1,x2,x3,x4)
|
136
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+
|
137
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+
#print("abcd", a,b,c,d)
|
138
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+
|
139
|
+
#print("Aの長さ", A)
|
140
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+
|
141
|
+
#print("Bの長さ",B)
|
142
|
+
|
143
|
+
#print("Cの長さ",C)
|
144
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+
|
145
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+
|
146
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+
|
147
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+
if A < B:
|
148
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+
|
149
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+
min = A
|
150
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+
|
151
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+
else:
|
152
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+
|
153
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+
min = B
|
154
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+
|
155
|
+
if C < min:
|
156
|
+
|
157
|
+
min = C
|
158
|
+
|
159
|
+
print("最小",min)
|
160
|
+
|
161
|
+
if 5 < min < 25:
|
162
|
+
|
125
|
-
im = cv2.drawContours(img_src,[box],0,(0,255,0),2)
|
163
|
+
im = cv2.drawContours(img_src,[box],0,(0,255,0),2)
|
126
164
|
|
127
165
|
|
128
166
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|
3
画像の挿入
test
CHANGED
File without changes
|
test
CHANGED
@@ -1,4 +1,6 @@
|
|
1
|
+
![イメージ説明](af90568d86afbbd802d0a1a1a7166b27.jpeg)
|
2
|
+
|
1
|
-
|
3
|
+
![リスト](5f231c7b127334bc591e3a97ce5cbb53.jpeg)
|
2
4
|
|
3
5
|
|
4
6
|
|
@@ -62,11 +64,27 @@
|
|
62
64
|
|
63
65
|
```python
|
64
66
|
|
65
|
-
|
67
|
+
import cv2
|
66
68
|
|
67
|
-
|
69
|
+
import math
|
68
70
|
|
69
|
-
|
71
|
+
import numpy as np
|
72
|
+
|
73
|
+
|
74
|
+
|
75
|
+
img_src = cv2.imread("./haku/sample/image1.ppm")
|
76
|
+
|
77
|
+
|
78
|
+
|
79
|
+
gauss = cv2.GaussianBlur(img_src,(11,11),0)#9,9
|
80
|
+
|
81
|
+
gray = cv2.cvtColor(gauss,cv2.COLOR_BGR2GRAY)
|
82
|
+
|
83
|
+
ret,th1 = cv2.threshold(gray,200,255,cv2.THRESH_BINARY)
|
84
|
+
|
85
|
+
edges = cv2.Canny(th1,50,150)#(100,150)
|
86
|
+
|
87
|
+
|
70
88
|
|
71
89
|
#矩形検出
|
72
90
|
|
2
コードの追加
test
CHANGED
File without changes
|
test
CHANGED
@@ -57,3 +57,97 @@
|
|
57
57
|
これは条件文に対してX1がどの値かが明確ではないため起こる問題であっていますでしょうか
|
58
58
|
|
59
59
|
この場合条件文で比較するためのアドバイスをいただけたら幸いです
|
60
|
+
|
61
|
+
|
62
|
+
|
63
|
+
```python
|
64
|
+
|
65
|
+
.
|
66
|
+
|
67
|
+
.
|
68
|
+
|
69
|
+
.
|
70
|
+
|
71
|
+
#矩形検出
|
72
|
+
|
73
|
+
img, contours, hierarchy = cv2.findContours(th1, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_L1)
|
74
|
+
|
75
|
+
if len(contours) > 0:
|
76
|
+
|
77
|
+
for i in range(0, len(contours)):
|
78
|
+
|
79
|
+
cnt = contours[i]
|
80
|
+
|
81
|
+
M = cv2.moments(cnt)
|
82
|
+
|
83
|
+
#print(M)
|
84
|
+
|
85
|
+
area = cv2.contourArea(cnt)
|
86
|
+
|
87
|
+
print(area)
|
88
|
+
|
89
|
+
if 500 < area < 5000:
|
90
|
+
|
91
|
+
rect = cv2.minAreaRect(contours[i])
|
92
|
+
|
93
|
+
box = cv2.boxPoints(rect)
|
94
|
+
|
95
|
+
box = np.int0(box)
|
96
|
+
|
97
|
+
x1,x2,x3,x4 = np.int0(box)
|
98
|
+
|
99
|
+
a = np.array(x1)
|
100
|
+
|
101
|
+
b = np.array(x2)
|
102
|
+
|
103
|
+
c = np.array(x3)
|
104
|
+
|
105
|
+
d = np.array(x4)
|
106
|
+
|
107
|
+
im = cv2.drawContours(img_src,[box],0,(0,255,0),2)
|
108
|
+
|
109
|
+
|
110
|
+
|
111
|
+
#直線検出
|
112
|
+
|
113
|
+
LSD = cv2.createLineSegmentDetector()
|
114
|
+
|
115
|
+
lines, width, prec, nfa = LSD.detect(edges)
|
116
|
+
|
117
|
+
if lines is not None:
|
118
|
+
|
119
|
+
for i in range(len(lines)):
|
120
|
+
|
121
|
+
|
122
|
+
|
123
|
+
for x1,y1,x2,y2 in lines[i] :
|
124
|
+
|
125
|
+
cv2.line(img_src,(x1,y1),(x2,y2),(0,0,255),2)
|
126
|
+
|
127
|
+
X1 = (x1, y1)
|
128
|
+
|
129
|
+
X2 = (x2, y2)
|
130
|
+
|
131
|
+
print("X1", X1)
|
132
|
+
|
133
|
+
print("X2", X2)
|
134
|
+
|
135
|
+
|
136
|
+
|
137
|
+
jug1 = cv2.pointPolygonTest(rect, X1, False)
|
138
|
+
|
139
|
+
jug2 = cv2.pointPolygonTest(rect, X2, False)
|
140
|
+
|
141
|
+
print(jug1)
|
142
|
+
|
143
|
+
print(jug2)
|
144
|
+
|
145
|
+
.
|
146
|
+
|
147
|
+
.
|
148
|
+
|
149
|
+
.
|
150
|
+
|
151
|
+
```
|
152
|
+
|
153
|
+
コードが見づらくて申し訳ありません
|
1
誤字
test
CHANGED
File without changes
|
test
CHANGED
@@ -44,7 +44,7 @@
|
|
44
44
|
|
45
45
|
Traceback (most recent call last):
|
46
46
|
|
47
|
-
File "
|
47
|
+
File "○○○.py", line 101, in <module>
|
48
48
|
|
49
49
|
if a < X1 < b:
|
50
50
|
|