def scramble_blocks(mat_in,block_height,block_width, key): dim=numpy.shape(mat_in) #print(dim) blocks_vert=scipy.uint8((dim[0])/block_height) #number of rows of blocks blocks_hor=scipy.uint8((dim[1])/block_width) #number of columns of blocks #key is divided in two parts. #the most significant digits determine th shift in the rows, and the least significant digits determine shift in rows key_sr=scipy.floor(key/10000) #rows shifted_by key_sr key_sc=key-(key_sr*10000) matrix_of_matrices=numpy.zeros((blocks_vert,blocks_hor,block_height,block_width)) matrix_of_matrices2=numpy.zeros((blocks_vert,blocks_hor,block_height,block_width)) matrix_buf=numpy.zeros(dim) matrix_out=numpy.zeros(dim) for i in range (blocks_vert): for j in range (blocks_hor): matrix_of_matrices[int((i+j*key_sc)%blocks_vert),int((j+key_sr)%blocks_hor),:,:]=mat_in[i*block_height:int((i+1)*block_height),j*block_width:int((j+1)*block_width)] for i in range (blocks_vert): for j in range (blocks_hor): matrix_buf[i*block_height:(i+1)*block_height, j*block_width:(j+1)*block_width]=matrix_of_matrices[i,j,:,:] for j in range (blocks_hor): for i in range (blocks_vert): matrix_of_matrices2[int((i+key_sc)%blocks_vert),int((j+i*key_sr+7)%blocks_hor),:,:]=matrix_buf[i*block_height:int((i+1)*block_height),j*block_width:int((j+1)*block_width)] for i in range (blocks_vert): for j in range (blocks_hor): matrix_out[i*block_height:(i+1)*block_height, j*block_width:(j+1)*block_width]=matrix_of_matrices2[i,j,:,:] return matrix_out
def test_compare_two(placer):
tile = scipy.array(Image.open("./eye.jpg"))
tile = resize_chunk(target, placer.compareChunkSize)
cand = scipy.array(Image.open("./imgs0/img_0gxHKNvoka.jpg"))
ID, best_pos, bestCorr = placer.compare(tile, [cand])
idx = best_pos
result = scipy.zeros(cand.shape)
result[idx[0]:idx[0]+50, idx[1]:idx[1]+50] = tile
Image.fromarray(scipy.uint8(result)).show()
Image.fromarray(scipy.uint8(cand)).show()
def filtro(P,vec):
if P==1:
filtromediana = scipy.ones((3, 3)) / 9
filtromediana = scipy.signal.convolve2d(vec, filtromediana, mode='same')
filtro = scipy.uint8(filtromediana)
####GAUSSIANO#####
else:
filtro = scipy.ndimage.gaussian_filter(vec, 2)
return filtro
def test_img_reconstr(placer):
img_obj = Image.open("Matilda.JPG")
img = scipy.array(img_obj)
img_obj.show()
data = placer.pack(img, 0)
img_r = placer.unpack(data, img.shape)
img_recon = Image.fromarray(scipy.uint8(img_r))
img_recon.show()
def test_compare_many(placer, target_fn, cnt):
target = scipy.array(Image.open(target_fn))
resizedTarget = resize_chunk(target, placer.compareChunkSize)
cand_names = os.listdir("./imgs0/")
cands = []
for i in range(cnt):
cands.append(scipy.array(Image.open("./imgs0/" + cand_names[i])))
if (cands[i].ndim == 2):
csh = cands[i].shape
cands[i] = scipy.reshape(cands[i], (csh[0], csh[1], 1))
resizedCands = placer.resizeTiles(scipy.array(cands))
ID, best_pos, bestCorr = placer.compare(resizedTarget, resizedCands)
cand = cands[ID]
idx = best_pos
result = scipy.zeros((75,75,3))
result[idx[0]:idx[0]+50, idx[1]:idx[1]+50] = target
Image.fromarray(scipy.uint8(result)).show()
Image.fromarray(scipy.uint8(cand)).show()
use_cam = True
if use_cam:
box=(rect[0]+5, rect[1]+5, rect[2]-5,rect[3]-5) # contract region to avoid including border
cap = cv2.VideoCapture(0)
while True:
ret,camimg = cap.read()
cv2.rectangle(camimg,(rect[0],rect[1]),(rect[2],rect[3]),(0,255,0),1)
cv2.imshow('video',camimg)
key = cv2.waitKey(10)
if key == 27: # esc key
exit()
if ord('a')<=key<=ord('z') or key==ord(' '): #press any key to take image
camimg = Image.fromarray(uint8(camimg)).convert('L')
print camimg
camimg = camimg.crop(box)
camimg=array(camimg)
break
cap.release()
cv2.destroyAllWindows()
else:
camimg = Image.open("jakie.jpg") # open colour image
camimg = Image.fromarray(uint8(camimg)).convert('L') # convert image to monochrome - this works
camimg=array(camimg)
box=(0,0,len(camimg[0]), len(camimg))
def genImage(self):
self.img=Image.fromarray(scp.uint8(self.terrain))
use_cam = True
if use_cam:
box=(rect[0]+5, rect[1]+5, rect[2]-5,rect[3]-5) # contract region to avoid including border
cap = cv2.VideoCapture(0)
while True:
ret,camimg = cap.read()
cv2.rectangle(camimg,(rect[0],rect[1]),(rect[2],rect[3]),(0,255,0),1)
cv2.imshow('video',camimg)
key = cv2.waitKey(10)
if key == 27: # esc key
break
if ord('a')<=key<=ord('z') or key==ord(' '): #press any key to take image
camimg = Image.fromarray(uint8(camimg)).convert('L')
camimg = camimg.crop(box)
camimg=array(camimg)
break
cap.release()
cv2.destroyAllWindows()
else:
camimg = Image.open("jake.jpg") # open colour image
camimg = Image.fromarray(uint8(camimg)).convert('L') # convert image to monochrome - this works
camimg=array(camimg)
box=(0,0,len(camimg[0]), len(camimg))
edges = camimg
box = (rect[0] + 5, rect[1] + 5, rect[2] - 5, rect[3] - 5
) # contract region to avoid including border
cap = cv2.VideoCapture(0)
while True:
ret, camimg = cap.read()
cv2.rectangle(camimg, (rect[0], rect[1]), (rect[2], rect[3]),
(0, 255, 0), 1)
cv2.imshow('video', camimg)
key = cv2.waitKey(10)
if key == 27: # esc key
exit()
if ord('a') <= key <= ord('z') or key == ord(
' '): #press any key to take image
camimg = Image.fromarray(uint8(camimg)).convert('L')
print camimg
camimg = camimg.crop(box)
camimg = array(camimg)
break
cap.release()
cv2.destroyAllWindows()
else:
camimg = Image.open("jakie.jpg") # open colour image
camimg = Image.fromarray(uint8(camimg)).convert(
'L') # convert image to monochrome - this works
camimg = array(camimg)
box = (0, 0, len(camimg[0]), len(camimg))