def predict(self):
if self.model is None:
self.build_model()
if not os.path.isdir(ROOT_PATH):
os.makedirs(ROOT_PATH)
path = TEST_PATH
files = list_files(path)
pix = []
for f in files:
pix_file = os.path.join(path, f)
pix_data = read_gray(pix_file)
pix.append(pix_data)
# print(pix_file)
pix = np.array(pix)
print("Test image max: ", np.amax(pix))
pix = pix / 255.0
print("Normalized image max: ", np.amax(pix))
ipix = np.expand_dims(pix, axis=3)
for i in range(ipix.shape[0]):
img = ipix[i]
img = np.expand_dims(img, axis=0)
out_pix = self.model.predict([img, img, img, img])
out_pix[out_pix >= self.thresh] = 1.0
out_pix[out_pix < self.thresh] = 0.0
out_pix = np.squeeze(out_pix) * 255.0
out_pix = out_pix.astype(np.uint8)
path = os.path.join(ROOT_PATH, files[i])
print("Saving ... ", path)
imsave(path, out_pix, cmap='gray')
def get_in_pix(filename="in_pix.npy", ispix=True, isskel=False, istest=False):
path = PX_PATH
if istest:
path = PT_PATH
if isskel:
path = SK_PATH
if not ispix:
path = path.replace("pixel", "point")
files = list_files(path)
pix = []
pmax = 0
pmin = 255
maxpts = 0
for f in files:
pix_file = os.path.join(path, f)
print(pix_file)
if ispix:
pix_data = read_gray(pix_file)
else:
image = np.zeros((256, 256), dtype=np.uint8)
pix_data = read_points(pix_file)
if len(pix_data) > maxpts:
maxpts = len(pix_data)
for p in pix_data:
if p[0] > pmax:
pmax = p[0]
if p[0] < pmin:
pmin = p[0]
if p[1] > pmax:
pmax = p[1]
if p[1] < pmin:
pmin = p[1]
x = min(round(p[0]), 255)
y = min(round(p[1]), 255)
image[x][y] = 255
impath = os.path.join("tmp", f + ".png")
print("Saving ... ", impath)
imsave(impath, image, cmap='gray')
pix_data = image
pix.append(pix_data)
# Max pts: 12270
print("Max pts: ", maxpts)
pix = np.array(pix)
print("Shape: ", pix.shape)
print("PMin: ", pmin)
print("PMax: ", pmax)
if not istest:
pix = np.expand_dims(pix, axis=3)
print("Final shape: ", pix.shape)
print("Min: ", np.amin(pix))
print("Max: ", np.amax(pix))
if not istest:
print("Saving to ", filename)
np.save(filename, pix)
return pix
def img2pt():
path = ROOT_PATH
if not os.path.isdir(PRED_PATH):
os.makedirs(PRED_PATH)
files = list_files(path)
pix = []
for f in files:
pix_file = os.path.join(path, f)
print(pix_file)
filename = pix_file
filename = filename.replace(".png", "")
filename = filename.replace("full", "skel")
filename = filename.replace("root", "pred")
print(filename)
pix_data = read_gray(pix_file)
with open(filename, "w+") as fh:
for x in range(pix_data.shape[0]):
for y in range(pix_data.shape[0]):
if pix_data[x][y]>0:
fh.write("%d %d\n" % (x, y))
def get_out_pix(filename="out_pix.npy"):
files = list_files(SK_PATH)
pix = []
for f in files:
pix_file = os.path.join(SK_PATH, f)
pix_data = read_gray(pix_file)
print(pix_file)
pix.append(pix_data)
pix = np.array(pix)
pix = np.mean(pix, axis=3)
pix = pix.astype(np.uint8)
print("Shape: ", pix.shape)
print("Uniques: ", np.unique(pix))
pix = np.expand_dims(pix, axis=3)
print("Final shape: ", pix.shape)
print("Min: ", np.amin(pix))
print("Max: ", np.amax(pix))
print("Saving to ", filename)
np.save(filename, pix)
return pix
def img2pt():
shutil.rmtree(PRED_PATH, ignore_errors=True)
path = ROOT_PATH
if not os.path.isdir(PRED_PATH):
os.makedirs(PRED_PATH)
files = list_files(path)
pix = []
for f in files:
pix_file = os.path.join(path, f)
print(pix_file)
filename = pix_file
filename = filename.replace(".png", "")
filename = filename.replace("full", "skel")
#filename = filename.replace(os.path.basename(os.path.normpath(ROOT_PATH)), "pred")
filename = os.path.join(PRED_PATH,
os.path.basename(os.path.normpath(filename)))
print(filename)
pix_data = read_gray(pix_file)
with open(filename, "w+") as fh:
for x in range(pix_data.shape[0]):
for y in range(pix_data.shape[0]):
if pix_data[x][y] > 0:
fh.write("%d %d\n" % (x, y))