def clip_reader(self, video_prefix):
"""Load frames in the clip.
Using openCV to load the clip frame by frame.
If specify the cropped size (crop_size > 0), randomly crop the clip.
Args:
index: Index of a video in the dataset.
Returns:
clip: A matrix (channel x depth x height x width) saves the pixels.
"""
clip = []
r1 = 0
framepath = os.path.join('/data/wjc/caffe_act1/data/UCF101', 'Flownet2_flow', video_prefix)
num_frames = len(glob.glob(framepath + '/*.flo'))
for i in xrange(num_frames):
filename = os.path.join(
'/data/wjc/caffe_act1/data/UCF101', 'Flownet2_flow', video_prefix,
'%05d.flo' % (i + 1))
# print (filename)
im = fl.read_flow(filename)
im[:,:,0]=(im[:,:,0]-np.min(im[:,:,0]))/(np.max(im[:,:,0])-np.min(im[:,:,0]))
im[:,:,1]=(im[:,:,1]-np.min(im[:,:,1]))/(np.max(im[:,:,1])-np.min(im[:,:,1]))
im = im * 255
# im = cv2.imread(filename)
if r1 == 0:
r1 = self._height / im.shape[0]
r2 = self._width / im.shape[1]
# im = cv2.resize(im, None, None, fx=r2, fy=r1,
# interpolation=cv2.INTER_LINEAR)
clip.append(im)
return [r1, r2], np.asarray(clip, dtype=np.uint8)
gt_number = count_text_lines(gt_flow_txt)
gt_paths = read_path(gt_flow_txt)
pred_number = count_text_lines(pred_flow_txt)
pred_paths = read_path(pred_flow_txt)
print(gt_number)
print(pred_number)
sum_AEE = []
count = 0
for i in range(gt_number):
pred_flow = fl.read_flow(pred_paths[i])
gt_flow = fl.read_flow(gt_paths[i])
res = fl.evaluate_flow(gt_flow, pred_flow)
# sum_AEE.append(res)
# count += 1
if res < 50:
sum_AEE.append(res)
count += 1
print('running file, aee is {}'.format(res))
AEE = np.mean(sum_AEE)
#! /usr/bin/python
# Author: Ruoteng Li
# Date: 6th Aug 2016
"""
Demo.py
This file demonstrates how to use kittitool module to read
and visualize flow file saved in kitti format .png
"""
from lib import flowlib as fl
# read kitti format optical flow file (.png)
print("Visualizing KITTI flow example ...")
flow_file_KITTI = 'data/example/KITTI/flow_gt.png'
flow_KITTI = fl.read_flow(flow_file_KITTI)
fl.visualize_flow(flow_KITTI)
# read Middlebury format optical flow file (.flo)
print("Visualizing Middlebury flow example ...")
flow_file_Middlebury = 'data/example/Middlebury/flow_gt.flo'
flow_Middlebury = fl.read_flow(flow_file_Middlebury)
fl.visualize_flow(flow_Middlebury)
#! /usr/bin/python
# Author: Ruoteng Li
# Date: 6th Aug 2016
"""
Demo.py
This file demonstrates how to use kittitool module to read
and visualize flow file saved in kitti format .png
"""
from lib import flowlib as fl
for i in range(4999, 5000):
# read Middlebury format optical flow file (.flo)
print "Visualizing Middlebury flow example ..."
flow_file_Middlebury = ('./data/ChairsSDHom/data/train1/flow/00003.flo')
flow_Middlebury = fl.read_flow(flow_file_Middlebury)
fl.visualize_flow(flow_Middlebury)
print "Visualizing Middlebury flow example ..."
flow_file_Middlebury1 = ('flownetc-pred-000%d.flo' % i)
flow_Middlebury1 = fl.read_flow(flow_file_Middlebury1)
fl.visualize_flow(flow_Middlebury1)
if not os.path.exists(output_dir):
os.mkdir(output_dir)
img1_input = f1.readlines()
img2_input = f2.readlines()
flow_input = f.readlines()
# Generate
for i in range(length):
x_locations = np.random.randint(0, canvas_width - patch_width, size=10)
y_locations = np.random.randint(0, canvas_height - patch_height, size=10)
img1 = Image.open(img1_input[i].strip())
img2 = Image.open(img2_input[i].strip())
if flow_input[i].strip().find('.png') != -1:
flow = kittitool.flow_read(flow_input[i].strip())
else:
flow = fl.read_flow(flow_input[i].strip())
for (x, y) in zip(x_locations, y_locations):
patch_img1 = img1.crop((x, y, x+patch_width, y+patch_height))
patch_img2 = img2.crop((x, y, x+patch_width, y+patch_height))
patch_flow = flow[y:y+patch_height, x:x+patch_width]
filename = str.format('%05d_' % i) + str(x) + '_' + str(y)
path1 = os.path.join(output_dir, filename + '_img1.png')
path2 = os.path.join(output_dir, filename + '_img2.png')
flow_path = os.path.join(output_dir, filename + '.flo')
patch_img1.save(path1)
patch_img2.save(path2)
fl.write_flow(patch_flow, flow_path)
g1.write(path1 + '\n')
g2.write(path2 + '\n')
g.write(flow_path + '\n')
if not args.flow_format:
args.flow_format = '.flo'
file_list = []
in_dir = os.path.abspath(args.input_dir)
out_dir = os.path.abspath(args.output_dir)
flow_count = 0
image_count = 0
for root, dirs, files in os.walk(in_dir):
if files:
for filename in files:
file_path = os.path.join(in_dir, root + '/' + filename)
if filename.find(args.flow_format) != -1:
# this is flow file
image_count += 1
print 'image count: ', image_count
flow = fl.read_flow(file_path)
new_flow = flow[args.y - 1:args.y + args.h - 1,
args.x - 1:args.x - 1 + args.w, :]
out_path = os.path.join(out_dir,
root[root.find('drive/') + 6:])
if not os.path.exists(out_path):
os.makedirs(out_path)
fl.write_flow(new_flow, os.path.join(out_path, filename))
elif filename.find(args.image_format) != -1:
# this is an image file
flow_count += 1
print 'flow count: ', flow_count
img = Image.open(file_path)
new_img = img.crop((args.x - 1, args.y - 1,
args.x + args.h - 1, args.y + args.w - 1))
out_path = os.path.join(out_dir,
# Author: Ruoteng Li
# Date: 6th Aug 2016
"""
Demo.py
This file demonstrates how to use kittitool module to read
and visualize flow file saved in kitti format .png
"""
from lib import flowlib as fl
import cv2
import numpy as np
# read kitti format optical flow file (.png)
print("Visualizing KITTI flow example ...")
flow_file_KITTI = './data/example/KITTI/flow-000000_10.flo'
flow_KITTI = fl.read_flow(flow_file_KITTI)
flow = cv2.imread(flow_file_KITTI)
#print(flow[:,:,2])
#
# invalid_idx = (flow[:, :, 0] == 0)
#
# flow[:, :, 0:2] = (flow[:, :, 0:2] - 2 ** 15) / 64.0
# flow[invalid_idx, 2] = 0
# flow[invalid_idx, 1] = 0
#
# img = np.zeros((256, 512, 2))
#
# img[:,:,0]=flow[:,:,2]
gt_file_path = 'gt_kitti_2015_flow.txt'
pred_file_path = 'pred_kitti_flow_EPIC.txt'
num_sample = count_text_lines(gt_file_path)
gt_paths = read_path(gt_file_path)
pred_path = read_path(pred_file_path)
print(num_sample)
sum_AEE = []
count = 0
for i in range(200):
gt_flow1 = fl.read_flow(gt_paths[i])
pre_flow1 = fl.read_flow(pred_path[i])
res = fl.evaluate_flow(gt_flow1, pre_flow1)
if res < 50:
sum_AEE.append(res)
count += 1
#sum_AEE.append(res)
print('running {}/{} file, aee is {}'.format(i + 1, num_sample, res))
AEE = np.mean(sum_AEE)
if not os.path.exists(output_dir):
os.mkdir(output_dir)
img1_input = f1.readlines()
img2_input = f2.readlines()
flow_input = f.readlines()
# Generate
for i in range(length):
x_locations = np.random.randint(0, canvas_width - patch_width, size=10)
y_locations = np.random.randint(0, canvas_height - patch_height, size=10)
img1 = Image.open(img1_input[i].strip())
img2 = Image.open(img2_input[i].strip())
if flow_input[i].strip().find('.png') != -1:
flow = kittitool.flow_read(flow_input[i].strip())
else:
flow = fl.read_flow(flow_input[i].strip())
for (x, y) in zip(x_locations, y_locations):
patch_img1 = img1.crop((x, y, x+patch_width, y+patch_height))
patch_img2 = img2.crop((x, y, x+patch_width, y+patch_height))
patch_flow = flow[y:y+patch_height, x:x+patch_width]
filename = str.format('%05d_' % i) + str(x) + '_' + str(y)
path1 = os.path.join(output_dir, filename + '_img1.png')
path2 = os.path.join(output_dir, filename + '_img2.png')
flow_path = os.path.join(output_dir, filename + '.flo')
patch_img1.save(path1)
patch_img2.save(path2)
fl.write_flow(patch_flow, flow_path)
g1.write(path1 + '\n')
g2.write(path2 + '\n')
g.write(flow_path + '\n')
segment_flow.py
This file convert flow file (.flo) into into flow class file according to the direction of the flow
Author: Li Ruoteng
Date: 16 Oct 2016
"""
import os
import argparse
import numpy as np
from PIL import Image
from lib import flowlib as fl
parser = argparse.ArgumentParser(description='Segment optical flow by orientation')
parser.add_argument('flow_format', type=str, help="The format of the files you want to search for")
parser.add_argument('input_dir', type=str, help="The directory to search for flow files")
parser.add_argument('--output_dir', type=str, help='the output directory')
args = parser.parse_args()
if args.output_dir:
args.output_dir = './segment_flow/'
if not os.path.exists(args.output_dir):
os.mkdir(args.output_dir)
for file_name in os.listdir(args.input_dir):
if file_name.find(args.flow_format) != -1:
flow = fl.read_flow(os.path.join(args.input_dir, file_name))
seg = fl.flow_to_segment(flow)
seg_img = Image.fromarray(seg.astype(np.uint8))
seg_img.save(os.path.join(args.output_dir, file_name[0:file_name.find(args.flow_format)] + '.png'))
name = name.split('.')[0]
pred_flow_names.append(name)
sum_AEE = []
count = 0
for pred_name in pred_flow_names:
for gt_path in gt_paths:
if (pred_name in gt_path) and (pred_name != 'Venus'):
count += 1
print(pred_name)
pred_flow = fl.read_flow(pred_flow_dir + '_' + pred_name + '.flo')
gt_flow = fl.read_flow(gt_path)
fl.visualize_flow(pred_flow)
fl.visualize_flow(gt_flow)
res = fl.evaluate_flow(gt_flow, pred_flow)
sum_AEE.append(res)
print('running file, aee is {}'.format(res))
AEE = np.mean(sum_AEE)
print('the averge error is {}'.format(AEE))
print(count)
#! /usr/bin/python
# Author: Ruoteng Li
# Date: 6th Aug 2016
"""
Demo.py
This file demonstrates how to use kittitool module to read
and visualize flow file saved in kitti format .png
"""
from lib import flowlib as fl
print("Visualizing driving dataset ...")
flow_file_drive = 'data/example/driving/0401.pfm'
flow_file_drive = fl.read_flow(flow_file_drive)
fl.visualize_flow(flow_file_drive)
# # read kitti format optical flow file (.png)
# print("Visualizing KITTI flow example ...")
# flow_file_KITTI = 'data/example/KITTI/flow_gt.png'
# flow_KITTI = fl.read_flow(flow_file_KITTI)
# fl.visualize_flow(flow_KITTI)
# # read Middlebury format optical flow file (.flo)
# print("Visualizing Middlebury flow example ...")
# flow_file_Middlebury = 'data/example/Middlebury/flow_gt.flo'
# flow_Middlebury = fl.read_flow(flow_file_Middlebury)
# fl.visualize_flow(flow_Middlebury)
if not args.flow_format:
args.flow_format = '.flo'
file_list = []
in_dir = os.path.abspath(args.input_dir)
out_dir = os.path.abspath(args.output_dir)
flow_count = 0
image_count = 0
for root, dirs, files in os.walk(in_dir):
if files:
for filename in files:
file_path = os.path.join(in_dir, root + '/' + filename)
if filename.find(args.flow_format) != -1:
# this is flow file
image_count += 1
print 'image count: ', image_count
flow = fl.read_flow(file_path)
new_flow = flow[args.y-1:args.y+args.h-1, args.x-1:args.x-1+args.w, :]
out_path = os.path.join(out_dir, root[root.find('drive/')+6:])
if not os.path.exists(out_path):
os.makedirs(out_path)
fl.write_flow(new_flow, os.path.join(out_path, filename))
elif filename.find(args.image_format) != -1:
# this is an image file
flow_count += 1
print 'flow count: ', flow_count
img = Image.open(file_path)
new_img = img.crop((args.x-1, args.y-1, args.x+args.h-1, args.y+args.w-1))
out_path = os.path.join(out_dir, root[root.find('drive/')+6:])
if not os.path.exists(out_path):
os.makedirs(out_path)
new_img.save(os.path.join(out_path, filename))
segment_flow.py
This file convert flow file (.flo) into into flow class file according to the direction of the flow
Author: Li Ruoteng
Date: 16 Oct 2016
"""
import os
import argparse
import numpy as np
from PIL import Image
from lib import flowlib as fl
parser = argparse.ArgumentParser(description='Segment optical flow by orientation')
parser.add_argument('flow_format', type=str, help="The format of the files you want to search for")
parser.add_argument('input_dir', type=str, help="The directory to search for flow files")
parser.add_argument('--output_dir', type=str, help='the output directory')
args = parser.parse_args()
if args.output_dir:
args.output_dir = './segment_flow/'
if not os.path.exists(args.output_dir):
os.mkdir(args.output_dir)
for file_name in os.listdir(args.input_dir):
if file_name.find(args.flow_format) != -1:
flow = fl.read_flow(os.path.join(args.input_dir, file_name))
seg = fl.segment_flow(flow)
seg_img = Image.fromarray(seg.astype(np.uint8))
seg_img.save(os.path.join(args.output_dir, file_name[0:file_name.find(args.flow_format)] + '.png'))