def draw(comp, base, fine, W=3000, H=2000):
arr = np.zeros((H,W,3), np.uint8)
segs = reduce(lambda x,y: x+y, [X.getArrangement().getSequencePreview().segs for X in comp.rhythms])
out_t = 0
duration = max([X.start+X.duration for X in segs])
for seg in segs:
cv2.line(arr,
(int(W*(out_t/duration)), 0),
(int(W*(seg.start/duration)), H),
(255,255,255))
out_t += seg.duration
base = cv2.resize(numm.image2np(base), (W,H))
fine = cv2.resize(numm.image2np(fine), (W,H))
divisors = np.linspace(0, 1, H).reshape((-1,1,1))
comp = ((base*(1-divisors)) + (fine*divisors)).astype(np.uint8)
numm.np2image(comp, 'COMP.PNG')
comp[arr==0] = 0
return comp
def draw(comp, base, fine, W=3000, H=2000):
arr = np.zeros((H, W, 3), np.uint8)
segs = reduce(
lambda x, y: x + y,
[X.getArrangement().getSequencePreview().segs for X in comp.rhythms])
out_t = 0
duration = max([X.start + X.duration for X in segs])
for seg in segs:
cv2.line(arr, (int(W * (out_t / duration)), 0),
(int(W * (seg.start / duration)), H), (255, 255, 255))
out_t += seg.duration
base = cv2.resize(numm.image2np(base), (W, H))
fine = cv2.resize(numm.image2np(fine), (W, H))
divisors = np.linspace(0, 1, H).reshape((-1, 1, 1))
comp = ((base * (1 - divisors)) + (fine * divisors)).astype(np.uint8)
numm.np2image(comp, 'COMP.PNG')
comp[arr == 0] = 0
return comp
import compose
def draw(comp, cover, W=1200, H=600):
arr = np.zeros((H,W,3), np.uint8)
covarr = cv2.resize(cover, (W,H))
segs = reduce(lambda x,y: x+y, [X.getArrangement().getSequencePreview().segs for X in comp.rhythms])
count = 0
duration = max([X.start+X.duration for X in segs])
total = W*H
temparr = []
temparr2 = []
for i in range(len(covarr)):
temparr.extend(covarr[i][:][:])
for seg in segs:
a = int(total*(seg.start/duration))
b = int(total*((seg.start+seg.duration)/duration))
temparr2.extend(temparr[a:b])
for j in range(H):
for i in range(W):
if count < len(temparr2)-1:
arr[j][i] = temparr2[count]
count+=1
else: break
return arr
if __name__=='__main__':
import sys
comp = compose.Composition.fromfile(sys.argv[1])
cover = numm.image2np(sys.argv[2])
numm.np2image(draw(comp, cover), sys.argv[3])
covarr = cv2.resize(cover, (W, H))
segs = reduce(
lambda x, y: x + y,
[X.getArrangement().getSequencePreview().segs for X in comp.rhythms])
count = 0
duration = max([X.start + X.duration for X in segs])
total = W * H
temparr = []
temparr2 = []
for i in range(len(covarr)):
temparr.extend(covarr[i][:][:])
for seg in segs:
a = int(total * (seg.start / duration))
b = int(total * ((seg.start + seg.duration) / duration))
temparr2.extend(temparr[a:b])
for j in range(H):
for i in range(W):
if count < len(temparr2) - 1:
arr[j][i] = temparr2[count]
count += 1
else:
break
return arr
if __name__ == '__main__':
import sys
comp = compose.Composition.fromfile(sys.argv[1])
cover = numm.image2np(sys.argv[2])
numm.np2image(draw(comp, cover), sys.argv[3])
import numm
import cv2
import numpy as np
import pickle
PATH = "a.png"
# PATH = 'b.png'
net = numm.image2np(PATH)
MOUSEX = 0
MOUSEY = 0
PX = 0
PY = 0
OFFX = 0
OFFY = 0
CIRCLES = []
EDGES = []
def find_circles(img, cutoff=125, blur=10, min_area=2, max_area=50):
blur = cv2.blur(img, (blur, blur))
blur = blur.mean(axis=2)
threshold = (blur < cutoff).astype(np.uint8)
contours, hierarchy = cv2.findContours(threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
circles = [cv2.minEnclosingCircle(X) for X in contours]
circles = filter(lambda (xy, r): r * 2 * np.pi >= min_area and r * 2 * np.pi <= max_area, circles)