basic firebrand recognition

Co-authored-by: Alex <AlexanderMcDowell@users.noreply.github.com>

examples/pyrometry/edge_detection.py

@@ -28,7 +28,11 @@ gray = cv.copyMakeBorder(
     value=0
 )
 
-contours = measure.find_contours(array=gray, level=100)
+# cv.imshow('gray', gray)
+# cv.waitKey(0)
+
+# contours = measure.find_contours(array=gray, level=100)
+_img, contours = cv.findContours(gray, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)[0]
 
 fig, ax = plt.subplots()
 ax.imshow(gray, cmap=plt.cm.gray, alpha=1)
@@ -36,14 +40,37 @@ ax.imshow(gray, cmap=plt.cm.gray, alpha=1)
 def calculate_area(countour):
     c = np.expand_dims(countour.astype(np.float32), 1)
     c = cv.UMat(c)
-    
+
     return cv.contourArea(c)
 
+def center_of_mass(X):
+    x = X[:,0]
+    y = X[:,1]
+    g = (x[:-1]*y[1:] - x[1:]*y[:-1])
+    A = 0.5*g.sum()
+    cx = ((x[:-1] + x[1:])*g).sum()
+    cy = ((y[:-1] + y[1:])*g).sum()
+
+    return 1./(6*A)*np.array([cx,cy])
+
+
+img_new = cv.cvtColor(gray, cv.COLOR_GRAY2BGR)
+
 for contour in contours:
     area = calculate_area(contour)
-    
-    if calculate_area(contour) > 250:
-        ax.plot(contour[:, 1], contour[:, 0], linewidth=0.5, color='orangered')
+
+    # if area > 250:
+        # cnt = np.array(contour).reshape((-1, 1, 2)).astype(np.int32)
+        # cv.drawContours(img_new, [cnt], -1, (0, 200, 255), thickness=10)
+
+    cv.drawContours(img_new, [contour], -1, (0, 200, 255), thickness=3)
+
+        # ax.plot(contour[:, 1], contour[:, 0], linewidth=0.5, color='orangered')
+
+# cv.imshow('contours', img_new)
+# cv.waitKey(0)
+
+cv.imwrite("firebrand_contours_opencv.png", img_new)
 
 ax.axis('image')
 ax.set_xticks([])