Merge branch 'master' of https://git.turtlebasket.ml/datadonkey-com/berkeley-firelab-general

examples/projected-area/projected_area.py

@@ -0,0 +1,80 @@
+import cv2 as cv
+import numpy as np
+from skimage import measure, morphology, color, segmentation
+import matplotlib.pyplot as plt
+
+file = 'proj-area-3.jpg'
+
+original = cv.imread(file)
+original = cv.cvtColor(original, cv.COLOR_BGR2RGB)
+img = original
+
+img = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+
+retval, thresh_gray = cv.threshold(img, 200, 255, cv.THRESH_BINARY)
+
+def remove_dirt(image):
+    image = morphology.area_closing(image, area_threshold=250, connectivity=1)
+    # image = morphology.opening(image, morphology.square(5))
+
+    return image
+
+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 = remove_dirt(thresh_gray)
+
+
+# alpha = 1 # Contrast control (1.0-3.0)
+# beta = 1 # Brightness control (0-100)
+
+# img = cv.convertScaleAbs(img, alpha=alpha, beta=beta)
+
+# img = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+
+# img = cv.medianBlur(img, 5)
+
+# retval, thresh_gray = cv.threshold(img, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)
+
+
+# img = cv.medianBlur(img, 5)
+
+# img = cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY_INV, 51, 15)
+
+contours = measure.find_contours(array=img, level=100)
+
+fig, ax = plt.subplots()
+ax.imshow(img, cmap=plt.cm.gray, alpha=0)
+
+index = 1
+
+for contour in contours:
+    if calculate_area(contour) > 300:
+        ax.plot(contour[:, 1], contour[:, 0], linewidth=0.5, color='orangered')
+
+        cX, cY = center_of_mass(contour)
+
+        plt.text(cY, cX, index, color='black', fontsize=6)
+
+        index += 1
+
+ax.axis('image')
+ax.set_xticks([])
+ax.set_yticks([])
+
+plt.savefig('output.png', dpi=300)
+
+# cv.imwrite('proj-area-1-processed.jpg', remove_dirt(img))