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main1.py
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#coding:utf-8
from renderer import Renderer
#from utils import
import numpy as np
import cv2
from PIL import Image
from utils import precompute_projections,create_pose
from os.path import join
from model import Model3D
from os import listdir
from os.path import isfile, join
nb_bg_images = 1500 # JUST FOR TEST
#nb_bg_images = 150000 # USE THIS NUMBER TO TRAIN BB8
# Image window size
c = 3
h = 480
w = 640
background_images = np.zeros((nb_bg_images, h, w, c), dtype='uint8')
bg_path = '/home/sky/Project/BB8-J15-master/data/BG/ImageNet'
def get_all_files(directory):
files = []
for f in listdir(directory):
if isfile(join(directory, f)):
files.append(join(directory, f))
else:
files.extend(get_all_files(join(directory, f)))
return files
def load_bgs_to_memory():
bg_file_names = get_all_files(bg_path)
print("{0} background images are found".format(len(bg_file_names)))
print('loading background images to memory...')
bg_nb, bg_h, bg_w = background_images.shape[:3]
for bg_idx in range(bg_nb):
random_bg_index = random.randint(0, len(bg_file_names) - 1)
bg = cv2.imread(bg_file_names[random_bg_index])
bg = cv2.resize(bg, (int(bg_w), int(bg_h)), interpolation=cv2.INTER_NEAREST)
background_images[bg_idx] = bg
printProgressBar(bg_idx, bg_nb, prefix = 'Progress:', suffix = 'Complete', length = 50)
printProgressBar(bg_nb, bg_nb, prefix = 'Progress:', suffix = 'Complete', length = 50)
#随机的产生两个角度，就可以唯一确定viewpoint,不不不，角度的，在球面不均匀
import math
#step1：
# 随机抽样产生一对均匀分布的随机数 u ，v ；这里u，v 在[-1,1] 范围内
# step2 ：
# 计算 r^2 = u^2+v^2;
# 如果 r^2 > 1 则重新抽样，直到满足 r^2 < 1 .
# step3 ：
# 计算
# x=2*u*sqrt(1-r2);
# y=2*v*sqrt(1-r2);
# z=1-2*r2;
ViewPoint = []
u_v = (2*np.random.rand(1000,3)-1)
#u_v = np.asarray([[0.6, 0.616 , 0.6],[1, 0, 0],[0,1,0],[0,0,1]])
#ViewPoint.append(u_v[0])
#ViewPoint.append(u_v[1])
#ViewPoint.append(u_v[2])
#ViewPoint.append(u_v[3])
for idx in range(0,1000,1):
u = u_v[idx][0]
v = u_v[idx][1]
r2 = u*u + v*v
if(r2 <1):
x = 2*u*math.sqrt(1-r2)
y = 2*v*math.sqrt(1-r2)
z = 1 - 2*r2
if(z >0.10 and y>0.40):
viewpoint = [x,y,z]
ViewPoint.append(viewpoint)
#添加
class bench:
def __init__(self):
self.cam = np.identity(3)
self.models = {}
Model_instance = bench()
Model_instance.cam[0, 0] = 680.0
Model_instance.cam[0, 2] = 320.0
Model_instance.cam[1, 1] = 680.0
Model_instance.cam[1, 2] = 240.0
Model_instance.cam[2, 2] = 1.0
#model file name
model_name = '1.ply'
Model_instance.models[model_name] = Model3D()
Model_instance.scale_to_meters = 0.01
#camera information
Model_instance.models[model_name].diameter = 125.64433088
Model_instance.models[model_name].load(model_name,scale = Model_instance.scale_to_meters)
#views = [0.6, 0616. , 0.6]
import os
w = 640
h = 480
#主要存储的文件，mask文件，可以根据深度值～=0,pose真值R,T，合成的RGB图像，bb8：8个顶点值
i = 0
ren = Renderer((w, h), Model_instance.cam)
for vp,views in enumerate(ViewPoint):
#print(views)
views = np.asarray(views)
for angle_deg in xrange(-30,30,10):
pose = create_pose(views, angle_deg=angle_deg)
zr = 2*np.random.rand(1,1) + 0.7
pose[:3, 3] = [0.0, 0., zr] # zr = 0.5
pose_path = join(os.path.dirname(__file__), 'pose')
content = pose_path + "/{:04d}".format(i)+ ".txt"
with open(content,'ab') as abc:
np.savetxt(abc,pose,delimiter=",")
abc.write("\n")
ren.draw_model(Model_instance.models[model_name],pose)
rgb,mask = ren.finish()
rgb_path = join(os.path.dirname(__file__),'Image')
mask_path = join(os.path.dirname(__file__), 'mask')
if(os.path.exists(rgb_path)):
rgb_name = rgb_path +"/"+"Render_{:04d}.jpg".format(i)
else:
os.mkdir(rgb_path)
rgb_name = rgb_path + "/"+"Render_{:04d}.jpg".format(i)
#print(name)
if(os.path.exists(mask_path)):
mask_name = mask_path +"/"+"mask_{:04d}.jpg".format(i)
else:
os.mkdir(mask_path)
mask_name = mask_path + "/"+"mask_{:04d}.jpg".format(i)
mask = (mask>0)*255
bg_idx = random_bg_index = random.randint(0, 1500)
bg_im = background_images[bg_idx]
i = i +1
cv2.imwrite(mask_name,mask)
cv2.imwrite(rgb_name, 255*rgb)
ren.clear()