def GenAndSaveWarp(A_list, B_list, flow_list, save_dir):
ids = [str(id_) for id_ in range(len(A_list))]
ratios = []
for id_, A_name, B_name, F_name in zip(ids, A_list, B_list, flow_list):
flow = read_gen(F_name)
A = read_gen(A_name)
B = read_gen(B_name)
A_Nwarp, A_Nwarp_mask = WarpNotEasy(A, flow, B)
ratio = np.sum(A_Nwarp_mask) / A_Nwarp_mask.size
A_Nwarp = A_Nwarp.astype(np.uint8)
A_Nwarpimg = Image.fromarray(A_Nwarp)
oname = os.path.join(save_dir, 'A_Nwarp' + str(id_) + '.png')
A_Nwarpimg.save(oname)
A_Nwarp_mask = A_Nwarp_mask.astype(np.uint8) * 255
A_Nwarp_maskimg = Image.fromarray(A_Nwarp_mask)
oname = os.path.join(save_dir, 'A_Nwarp_mask' + str(id_) + '.png')
A_Nwarp_maskimg.save(oname)
print(ratio)
ratios.append(ratio)
oname = os.path.join(save_dir, 'mask_ratios.txt')
save_list(oname, ratios)
def GenerateSparplots(self):
flowlist = self.outlist
gtflowlist = self.gtflow
self.aepes=[]
for i,flowname in enumerate(flowlist):
n,e = splitext(flowname)
resflowname = n + '_res' + e
flow = read_gen(flowname)
resflow = read_gen(resflowname)
gtflow = read_gen(gtflowlist[i])
_,_,_,aepe0=self.SparplotSimple(i,flow,resflow,gtflow)
self.aepes.append(aepe0)
print("整个数据集抽样平均AEPE: ",np.mean(self.aepes))
def GenerateSparplots(self):
assert (False == self.isempty)
flowlist = self.flows['outFlow']
gtflowlist = self.rawData['gtFlow']
resflowlist = self.flows['resFlow']
assert (len(flowlist) == len(gtflowlist) == len(resflowlist))
for i in range(len(flowlist)):
flow = read_gen(flowlist[i])
resflow = read_gen(resflowlist[i])
gtflow = read_gen(gtflowlist[i])
_, _, _, aepe0 = self.SparplotSimple(i, flow, resflow, gtflow)
self.aepes.append(aepe0)
self.avgAepe = np.mean(self.aepes)
print("整个数据集抽样平均AEPE: ", self.avgAepe)
def _GenWarp(self, keys):
flow_list = self.flows['outFlow']
A_list = self.rawData['imgA']
B_list = self.rawData['imgB']
assert len(flow_list) > 0
assert len(flow_list) == len(A_list) == len(B_list)
for i, F_name, in enumerate(flow_list):
A_name = A_list[i]
B_name = B_list[i]
flow = read_gen(F_name)
A = read_gen(A_name)
B = read_gen(B_name)
if ('warp' in keys or 'warpOverlay' in keys
or 'warpOverlayUsingMask' in keys):
A_warp = warp_easy(A, flow)
A_warp_mask = Mask(A_warp)
if ('newWarp' in keys or 'newWarpOverlay' in keys
or 'newWarpOverlayUsingMask' in keys):
A_Nwarp, A_Nwarp_mask = WarpNotEasy(A, flow,
B) #########A_Nwarp的定义需要修改
print('\rWarping... ',
str(i),
'/',
str(len(flow_list)),
end='Gen:')
for key in keys:
print(f'{key},', end='')
O_name = self.warpPics[key][i]
if ('warp' == key):
self.Warp(A_warp, B, O_name)
elif ('warpOverlay' == key):
self.WarpOverlay(A_warp, B, O_name)
elif ('warpOverlayUsingMask' == key):
self.WarpOverlayUsingMask(A_warp, A_warp_mask, B, O_name)
elif ('warpMask' == key):
self.SaveMask(A_warp_mask, O_name)
elif ('newWarp' == key):
self.Warp(A_Nwarp, B, O_name)
elif ('newWarpOverlay' == key):
self.WarpOverlay(A_Nwarp, B, O_name)
elif ('newWarpOverlayUsingMask' == key):
self.WarpOverlayUsingMask(A_Nwarp, A_Nwarp_mask, B, O_name)
elif ('newWarpMask' == key):
self.SaveMask(A_Nwarp_mask, O_name)
print('')
def VizGrayFlows(self, key, flowList):
imGrayList = self.flowVizsGray[key + 'Vizg']
assert len(flowList) == len(imGrayList)
if (len(flowList) == 0):
print('WARRING VizGrayFlows: Not find any flowfiles')
for flowName, imGrayName in zip(flowList, imGrayList):
flow = read_gen(flowName)
flow_g = abs_flow(flow)
imsave(imGrayName, flow_g / np.max(flow_g))
def VizColorFlows(self, key, flowList):
imList = self.flowVizs[key + 'Viz']
assert len(flowList) == len(imList)
if (len(flowList) == 0):
print('WARRING VizColorFlows: Not find any flowfiles')
for flowName, imName in zip(flowList, imList):
flow = read_gen(flowName)
flow_viz = Image.fromarray(viz_flow(flow))
imsave(imName, flow_viz)
def _GenWarp(self, keys):
flow_list = self.flows['outFlow']
A_list = self.rawData['imgA']
B_list = self.rawData['imgB']
assert len(flow_list) > 0
assert len(flow_list) == len(A_list) == len(B_list)
for i, F_name, in enumerate(flow_list):
A_name = A_list[i]
B_name = B_list[i]
flow = read_gen(F_name)
A = read_gen(A_name)
B = read_gen(B_name)
if ('warp' in keys or 'warpOverlay' in keys
or 'warpOverlayUsingMask' in keys):
A_warp = warp_easy(A, flow)
if ('newWarp' in keys or 'newWarpOverlay' in keys
or 'newWarpOverlayUsingMask' in keys):
res = WarpNotEasy(A, flow, B)
if len(res) == 2:
A_Nwarp, A_Nwarp_mask = res
else:
A_Nwarp = res
A_Nwarp_mask = Mask(A_Nwarp)
print('\r', str(i), '/', str(len(flow_list)), end='')
for key in keys:
O_name = self.warpPics[key][i]
if ('warp' == key):
self.Warp(A_warp, B, O_name)
elif ('warpOverlay' == key):
self.WarpOverlay(A_warp, B, O_name)
elif ('warpOverlayUsingMask' == key):
self.WarpOverlayUsingMask(A_warp, B, O_name, Mask(A_warp))
elif ('newWarp' == key):
self.Warp(A_Nwarp, B, O_name)
elif ('newWarpOverlay' == key):
self.WarpOverlay(A_Nwarp, B, O_name)
elif ('newWarpOverlayUsingMask' == key):
self.WarpOverlayUsingMask(A_Nwarp, B, O_name, A_Nwarp_mask)
elif ('newWarpMask' == key):
A_Nwarp_mask_ = A_Nwarp_mask.astype(np.uint8) * 255
A_Nwarp_mask__ = Image.fromarray(A_Nwarp_mask_)
A_Nwarp_mask__.save(O_name)
print('')
imgB = '0007.png'
gt = 'OpticalFlowIntoFuture_0006_L.pfm'
save_path = path #'../data/Tools/TEST_EPE/2'
p_imA = os.path.join(path, imgA)
s_imA = os.path.join(save_path, 'imgA.png')
p_imB = os.path.join(path, imgB)
s_imB = os.path.join(save_path, 'imgB.png')
p_gt = os.path.join(path, gt)
s_gt = os.path.join(save_path, 'gt.jpg')
if not os.path.exists(save_path):
os.makedirs(save_path)
print(f'Create {save_path}')
imA = cv2.imread(p_imA)
imB = cv2.imread(p_imB)
flow = read_gen(p_gt)
surf = cv2.xfeatures2d.SURF_create(800)
keypointA, descriptorA = surf.detectAndCompute(imA, None)
keypointB, descriptorB = surf.detectAndCompute(imB, None)
bastMacher = cv2.FlannBasedMatcher_create()
matches = bastMacher.match(descriptorA, descriptorB)
matches.sort(key=lambda m: m.distance)
goodmatch = matches[0:10]
imagePointsA = np.array([keypointA[m.queryIdx].pt for m in goodmatch])
imagePointsB = np.array([keypointB[m.trainIdx].pt for m in goodmatch])
h**o, mask = cv2.findHomography(imagePointsA, imagePointsB)
matchesMask = mask.ravel().tolist()
h, w = imA.shape[0:2]
imAwB = cv2.warpPerspective(imA, h**o, (w, h)) # (512, 384))
homoflow = GenFlowAB(h**o, (w, h))
# -*- coding: utf-8 -*-
import numpy as np
import sys
from PIL import Image
sys.path.append("../Server_EasyTest")
from myflowlib import read_gen, viz_flow
path = 'E:\\我的文档\\任务\\配准1\\测试图片\\展示在文档中的\\z1\\'
gt_name = 'z1f.flo'
res_name = 'z1res.flo'
A_name = 'z1A.jpg'
B_name = 'z1B.jpg'
gt_name = path + gt_name
A_name = path + A_name
B_name = path + B_name
res_name = path + res_name
gt = read_gen(gt_name)
A = read_gen(A_name)
B = read_gen(B_name)
res = read_gen(res_name)
res = np.sqrt(res[:, :, 0] * res[:, :, 0] + res[:, :, 1] * res[:, :, 1])
res = res > 0.14 * (np.max(res))
res = res.astype(np.uint8) * 255
resimg = Image.fromarray(res)
resimg.save(path + 'z1res_mask.png')
sys.path.append("../../Server_EasyTest")
from myflowlib import read_gen, viz_flow, WarpNotEasy, warp_easy
from yuyy_postprocess import warp_judge
if __name__ == '__main__':
path = '../../data/ds_v2/TEST5_1/'
gt_name = 'flow/2gtAB.flo'
A_name = 'show/2A.png'
B_name = 'show/2B.png'
gt_name = path + gt_name
A_name = path + A_name
B_name = path + B_name
gt = read_gen(gt_name)
A = read_gen(A_name)
B = read_gen(B_name)
# warp,mask = warp_judge(A,gt,B)
warp = WarpNotEasy(A, gt)
A_warpimg = Image.fromarray(warp)
A_warpimg.save(path + 'show/2AF.jpg')
gt_name = 'flow/2gtBA.flo'
A_name = 'show/2B.png'
B_name = 'show/2A.png'
gt_name = path + gt_name
A_name = path + A_name
B_name = path + B_name
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 4 16:31:24 2018
@author: Administrator
"""
import sys
from os.path import join
from scipy.misc import imsave,imread
from PIL import Image
import numpy as np
sys.path.append("../Server_EasyTest")
from myflowlib import read_gen,abs_flow
path= 'E:\我的文档\任务\配准1\测试图片\展示在文档中的\z3'
name = 'z3res.flo'
save_name ='z3res_gray.jpg'
name = join(path,name)
save_name = join(path,save_name)
res = read_gen(name)
res = abs_flow(res)
imsave(save_name,res/np.max(res))
import sys
from os.path import join
from PIL import Image
import numpy as np
sys.path.append("../Server_EasyTest")
from myflowlib import read_gen
path= 'E:\我的文档\任务\配准1\测试图片\展示在文档中的\z3'
Aforward_name = 'z3A_forward.png'
B_name = 'z3B.jpg'
save_name = 'z3_F.jpg'
Aforward_name = join(path,Aforward_name)
B_name = join(path,B_name)
save_name = join(path,save_name)
Af = read_gen(Aforward_name)
B = read_gen(B_name)
save = np.array(Af * 0.5+ B * 0.5)
save = save.astype(np.uint8)
saveimg = Image.fromarray(save)
saveimg.save(save_name)
