def main(f_p, f_n):
net = caffe.Net('../models/test_1/deploy.prototxt', '../outputs/snapshot_iter_2000.caffemodel', caffe.TEST)
im, im_p, im_n = fetch_flow_data('../data/training/final/'+f_p+'.png',
'../data/training/final/'+f_n+'.png')
net.blobs['data'].data.flat = im.flat
net.forward()
flow = net.blobs['flow_est'].data[0,...].transpose()
flow_img = pyflow.flow_to_color(flow)
gt = pyflow.read_flow_file('../data/training/flow/'+f_p+'.flo')
gt_img = pyflow.flow_to_color(gt)
f, axarr = plt.subplots(2, 2)
axarr[0, 0].imshow(im_p)
axarr[0, 0].set_title('frame_prev')
axarr[0, 1].imshow(im_n)
axarr[0, 1].set_title('frame_next')
axarr[1, 0].imshow(flow_img)
axarr[1, 0].set_title('result')
axarr[1, 1].imshow(gt_img)
axarr[1, 1].set_title('ground_truth')
f1, axarr1 = plt.subplots(2, 2)
axarr1[0, 0].imshow(flow[...,0], cmap=cm.gray_r)
axarr1[0, 0].set_title('flow_u')
axarr1[0, 1].imshow(gt[...,0], cmap=cm.gray_r)
axarr1[0, 1].set_title('ground_truth_u')
axarr1[1, 0].imshow(flow[...,1], cmap=cm.gray_r)
axarr1[1, 0].set_title('flow_v')
axarr1[1, 1].imshow(gt[...,1], cmap=cm.gray_r)
axarr1[1, 1].set_title('ground_truth_v')
plt.show()
def load_next_image(self):
if self._cur == len(self.data_list):
self._cur = 0
shuffle(self.data_list)
datum = self.data_list[self._cur]
self._cur += 1
im_p = np.asarray(Image.open(datum['im_p']))
im_n = np.asarray(Image.open(datum['im_n']))
#TODO Transformation image and flow here.
im = np.dstack([im_p, im_n])/255.0 - 0.5
fl = np.asarray(pyflow.read_flow_file(datum['fl']))
return im.transpose(), fl.transpose()
def main():
net = caffe.Net('../models/test_1/deploy.prototxt',
'../outputs/snapshot_iter_2000.caffemodel',
caffe.TEST)
sintel = MPISintel('../data/training')
idx = 0
for frame in sintel.train_list:
print frame['fl']
im, im_p, im_n = fetch_flow_data(frame['im_p'],
frame['im_n'])
net.blobs['data'].data.flat = im.flat
net.forward()
flow = net.blobs['flow_est'].data[0,...].transpose()
flow_img = pyflow.flow_to_color(flow)
gt = pyflow.read_flow_file(frame['fl'])
gt = cv2.resize(gt, (256, 109))
gt_img = pyflow.flow_to_color(gt)
err = pyflow.calc_epe_stat(flow, gt)
print err
"""test module"""
from __future__ import print_function
if __name__ == "__main__":
import sys
sys.path.insert(0, '../../')
from numpy.testing import assert_equal
import cv2
import pylab
import pyflow
flow = pyflow.read_flow_file(r"flow10.flo")
pyflow.write_flow_file("test.flo", flow)
g = pyflow.read_flow_file(r"test.flo")
assert_equal(flow, g)
img = pyflow.flow_to_color(flow)
pylab.imshow(img)
pylab.show()
pylab.imshow(pyflow.show_color_scheme())
pylab.show()
prev_frame = cv2.imread("frame10.png")
next_frame = cv2.imread("frame11.png")
prev_gray = cv2.cvtColor(prev_frame, cv2.COLOR_BGR2GRAY)
next_gray = cv2.cvtColor(next_frame, cv2.COLOR_BGR2GRAY)
fbflow = cv2.calcOpticalFlowFarneback(prev_gray, next_gray, 0.5, 3, 15, 3, 5, 1.2, 0)