dnc/Visualize/BitmapTask.py

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2018-11-16 03:31:23 +08:00
# Copyright 2017 Robert Csordas. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ==============================================================================
import numpy as np
try:
import cv2
except:
cv2=None
from Utils.Helpers import as_numpy
def visualize_bitmap_task(i_data, o_data, zoom=8):
if not isinstance(o_data, list):
o_data = [o_data]
imgs = []
for d in [i_data]+o_data:
if d is None:
continue
d=as_numpy(d)
if d.ndim>2:
d=d[0]
imgs.append(np.expand_dims(d.T*255, -1).astype(np.uint8))
img = np.concatenate(imgs, 0)
return nearest_zoom(img, zoom)
def visualize_01(t, zoom=8):
return nearest_zoom(np.expand_dims(t*255,-1).astype(np.uint8), zoom)
def nearest_zoom(img, zoom=1):
if zoom>1 and cv2 is not None:
return cv2.resize(img, (img.shape[1] * zoom, img.shape[0] * zoom), interpolation=cv2.INTER_NEAREST)
else:
return img
def concatenate_tensors(tensors):
max_size = None
dtype = None
for t in tensors:
s = t.shape
if max_size is None:
max_size = list(s)
dtype = t.dtype
continue
assert t.ndim ==len(max_size), "Can only concatenate tensors with same ndim."
assert t.dtype == dtype, "Tensors must have the same type"
max_size = [max(max_size[i], s[i]) for i in range(len(max_size))]
res = np.zeros([len(tensors)] + max_size, dtype=dtype)
for i, t in enumerate(tensors):
res[i][tuple([slice(0,t.shape[i]) for i in range(t.ndim)])] = t
return res