Contours ও Shape Detection

import cv2

img  = cv2.imread("coins.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (7,7), 0)
_, th = cv2.threshold(blur, 0, 255,
                      cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)

contours, hierarchy = cv2.findContours(
    th, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

print("Total objects:", len(contours))
cv2.drawContours(img, contours, -1, (0,255,0), 2)
cv2.imwrite("out.jpg", img)

import cv2

for c in contours:
    area  = cv2.contourArea(c)
    peri  = cv2.arcLength(c, True)
    x,y,w,h = cv2.boundingRect(c)
    (cx,cy), r = cv2.minEnclosingCircle(c)
    rect = cv2.minAreaRect(c)                # rotated rect

    if area < 200:           # noise filter
        continue

    aspect = w / h
    extent = area / (w*h)    # bounding box-এর কত % ভরা

import cv2

for c in contours:
    peri   = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.02 * peri, True)
    sides  = len(approx)

    if   sides == 3: name = "Triangle"
    elif sides == 4: name = "Square/Rect"
    elif sides == 5: name = "Pentagon"
    else:            name = "Circle/Other"

import cv2

hull = cv2.convexHull(c)
cv2.drawContours(img, [hull], -1, (255,0,0), 2)

# Hand gesture recognition-এর জন্য defect points
hull_idx = cv2.convexHull(c, returnPoints=False)
defects  = cv2.convexityDefects(c, hull_idx)

import cv2

count = 0
for c in contours:
    a = cv2.contourArea(c)
    if a < 500: continue
    count += 1
    (x,y), r = cv2.minEnclosingCircle(c)
    cv2.circle(img, (int(x),int(y)), int(r), (0,255,0), 2)
    cv2.putText(img, str(count), (int(x)-10,int(y)+5),
                cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,255), 2)
print("Total coins:", count)