declassify some projects

goose2function.py

@@ -0,0 +1,31 @@
+import cv2, numpy, matplotlib.pyplot as plt, scipy.interpolate, sys
+from collections import defaultdict
+
+img = cv2.imread(sys.argv[1]) 
+H, S, L = cv2.split(cv2.cvtColor(img, cv2.COLOR_BGR2HSV))
+img_blur = cv2.GaussianBlur(H, (15,15), 0) 
+thresh = cv2.threshold(img_blur, 55, 255, cv2.THRESH_BINARY)[1]
+edges = cv2.Canny(image=thresh, threshold1=100, threshold2=200)
+c, hier = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+best = max(c, key=lambda x: x.shape[0])[:, 0, :]
+min_x, max_x = min(best[:, 0]), max(best[:, 0])
+min_y, max_y = min(best[:, 1]), max(best[:, 1])
+xrange = max_x - min_x
+yrange = max_y - min_y
+coords = [[((x - min_x) / xrange) * 2 - 1, ((y - min_y) / yrange) * 2 - 1] for x, y in best ]
+coords.sort(key=lambda x: x[0])
+coords2 = defaultdict(list)
+for x, y in coords:
+    coords2[x].append(y)
+coords3x = []
+coords3y = []
+last = -1
+for x, ys in coords2.items():
+    coords3y.append(min(ys, key=lambda x: abs(x - last)))
+    coords3x.append(x)
+    last = coords3y[-1]
+i = scipy.interpolate.CubicSpline(coords3x, coords3y, extrapolate=True)
+xs = numpy.arange(-1.0, 1.0, 0.02)
+plt.plot(coords3x, coords3y, label='data')
+plt.plot(xs, i(xs))
+plt.show()