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ResultMerge_multi_process.py
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ResultMerge_multi_process.py
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"""
To use the code, users should to config detpath, annopath and imagesetfile
detpath is the path for 15 result files, for the format, you can refer to "http://captain.whu.edu.cn/DOTAweb/tasks.html"
search for PATH_TO_BE_CONFIGURED to config the paths
Note, the evaluation is on the large scale images
"""
import os
import numpy as np
import re
import time
import sys
sys.path.insert(0,'..')
try:
import dota_utils as util
except:
import dota_kit.dota_utils as util
import polyiou
import pdb
import math
from multiprocessing import Pool
from functools import partial
## the thresh for nms when merge image
nms_thresh = 0.1
def py_cpu_nms_poly(dets, thresh):
scores = dets[:, 8]
polys = []
areas = []
for i in range(len(dets)):
tm_polygon = polyiou.VectorDouble([dets[i][0], dets[i][1],
dets[i][2], dets[i][3],
dets[i][4], dets[i][5],
dets[i][6], dets[i][7]])
polys.append(tm_polygon)
order = scores.argsort()[::-1]
keep = []
while order.size > 0:
ovr = []
i = order[0]
keep.append(i)
for j in range(order.size - 1):
iou = polyiou.iou_poly(polys[i], polys[order[j + 1]])
ovr.append(iou)
ovr = np.array(ovr)
# print('ovr: ', ovr)
# print('thresh: ', thresh)
try:
if math.isnan(ovr[0]):
pdb.set_trace()
except:
pass
inds = np.where(ovr <= thresh)[0]
# print('inds: ', inds)
order = order[inds + 1]
return keep
def py_cpu_nms_poly_fast(dets, thresh):
obbs = dets[:, 0:-1]
x1 = np.min(obbs[:, 0::2], axis=1)
y1 = np.min(obbs[:, 1::2], axis=1)
x2 = np.max(obbs[:, 0::2], axis=1)
y2 = np.max(obbs[:, 1::2], axis=1)
scores = dets[:, 8]
areas = (x2 - x1 + 1) * (y2 - y1 + 1)
polys = []
for i in range(len(dets)):
tm_polygon = polyiou.VectorDouble([dets[i][0], dets[i][1],
dets[i][2], dets[i][3],
dets[i][4], dets[i][5],
dets[i][6], dets[i][7]])
polys.append(tm_polygon)
order = scores.argsort()[::-1]
keep = []
while order.size > 0:
ovr = []
i = order[0]
keep.append(i)
# if order.size == 0:
# break
xx1 = np.maximum(x1[i], x1[order[1:]])
yy1 = np.maximum(y1[i], y1[order[1:]])
xx2 = np.minimum(x2[i], x2[order[1:]])
yy2 = np.minimum(y2[i], y2[order[1:]])
# w = np.maximum(0.0, xx2 - xx1 + 1)
# h = np.maximum(0.0, yy2 - yy1 + 1)
w = np.maximum(0.0, xx2 - xx1)
h = np.maximum(0.0, yy2 - yy1)
hbb_inter = w * h
hbb_ovr = hbb_inter / (areas[i] + areas[order[1:]] - hbb_inter)
# h_keep_inds = np.where(hbb_ovr == 0)[0]
h_inds = np.where(hbb_ovr > 0)[0]
tmp_order = order[h_inds + 1]
for j in range(tmp_order.size):
iou = polyiou.iou_poly(polys[i], polys[tmp_order[j]])
hbb_ovr[h_inds[j]] = iou
# ovr.append(iou)
# ovr_index.append(tmp_order[j])
# ovr = np.array(ovr)
# ovr_index = np.array(ovr_index)
# print('ovr: ', ovr)
# print('thresh: ', thresh)
try:
if math.isnan(ovr[0]):
pdb.set_trace()
except:
pass
inds = np.where(hbb_ovr <= thresh)[0]
# order_obb = ovr_index[inds]
# print('inds: ', inds)
# order_hbb = order[h_keep_inds + 1]
order = order[inds + 1]
# pdb.set_trace()
# order = np.concatenate((order_obb, order_hbb), axis=0).astype(np.int)
return keep
def py_cpu_nms(dets, thresh):
"""Pure Python NMS baseline."""
#print('dets:', dets)
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
areas = (x2 - x1 + 1) * (y2 - y1 + 1)
## index for dets
order = scores.argsort()[::-1]
keep = []
while order.size > 0:
i = order[0]
keep.append(i)
xx1 = np.maximum(x1[i], x1[order[1:]])
yy1 = np.maximum(y1[i], y1[order[1:]])
xx2 = np.minimum(x2[i], x2[order[1:]])
yy2 = np.minimum(y2[i], y2[order[1:]])
w = np.maximum(0.0, xx2 - xx1 + 1)
h = np.maximum(0.0, yy2 - yy1 + 1)
inter = w * h
ovr = inter / (areas[i] + areas[order[1:]] - inter)
inds = np.where(ovr <= thresh)[0]
order = order[inds + 1]
return keep
def nmsbynamedict(nameboxdict, nms, thresh):
nameboxnmsdict = {x: [] for x in nameboxdict}
for imgname in nameboxdict:
#print('imgname:', imgname)
#keep = py_cpu_nms(np.array(nameboxdict[imgname]), thresh)
#print('type nameboxdict:', type(nameboxnmsdict))
#print('type imgname:', type(imgname))
#print('type nms:', type(nms))
keep = nms(np.array(nameboxdict[imgname]), thresh)
#print('keep:', keep)
outdets = []
#print('nameboxdict[imgname]: ', nameboxnmsdict[imgname])
for index in keep:
# print('index:', index)
outdets.append(nameboxdict[imgname][index])
nameboxnmsdict[imgname] = outdets
return nameboxnmsdict
def poly2origpoly(poly, x, y, rate):
origpoly = []
for i in range(int(len(poly)/2)):
tmp_x = float(poly[i * 2] + x) / float(rate)
tmp_y = float(poly[i * 2 + 1] + y) / float(rate)
origpoly.append(tmp_x)
origpoly.append(tmp_y)
return origpoly
def mergesingle(dstpath, nms, fullname):
name = util.custombasename(fullname)
#print('name:', name)
dstname = os.path.join(dstpath, name + '.txt')
with open(fullname, 'r') as f_in:
nameboxdict = {}
lines = f_in.readlines()
splitlines = [x.strip().split(' ') for x in lines]
for splitline in splitlines:
subname = splitline[0]
splitname = subname.split('__')
oriname = splitname[0]
pattern1 = re.compile(r'__\d+___\d+')
#print('subname:', subname)
x_y = re.findall(pattern1, subname)
x_y_2 = re.findall(r'\d+', x_y[0])
x, y = int(x_y_2[0]), int(x_y_2[1])
pattern2 = re.compile(r'__([\d+\.]+)__\d+___')
rate = re.findall(pattern2, subname)[0]
confidence = splitline[1]
poly = list(map(float, splitline[2:]))
origpoly = poly2origpoly(poly, x, y, rate)
det = origpoly
det.append(confidence)
det = list(map(float, det))
if (oriname not in nameboxdict):
nameboxdict[oriname] = []
nameboxdict[oriname].append(det)
nameboxnmsdict = nmsbynamedict(nameboxdict, nms, nms_thresh)
with open(dstname, 'w') as f_out:
for imgname in nameboxnmsdict:
for det in nameboxnmsdict[imgname]:
#print('det:', det)
confidence = det[-1]
bbox = det[0:-1]
outline = imgname + ' ' + str(confidence) + ' ' + ' '.join(map(str, bbox))
#print('outline:', outline)
f_out.write(outline + '\n')
def mergebase_parallel(srcpath, dstpath, nms):
"""
将源路径中所有的txt目标信息,经nms后存入目标路径中的同名txt
@param srcpath: 合并前信息保存的txt源路径
@param dstpath: 合并后信息保存的txt目标路径
@param nms: NMS函数
"""
pool = Pool(16)
filelist = util.GetFileFromThisRootDir(srcpath)
mergesingle_fn = partial(mergesingle, dstpath, nms)
# pdb.set_trace()
pool.map(mergesingle_fn, filelist)
def mergebase(srcpath, dstpath, nms):
filelist = util.GetFileFromThisRootDir(srcpath)
for filename in filelist:
mergesingle(dstpath, nms, filename)
def mergebyrec(srcpath, dstpath):
"""
srcpath: result files before merge and nms
dstpath: result files after merge and nms
"""
# srcpath = r'E:\bod-dataset\results\bod-v3_rfcn_2000000'
# dstpath = r'E:\bod-dataset\results\bod-v3_rfcn_2000000_nms'
mergebase(srcpath,
dstpath,
py_cpu_nms)
def mergebypoly(srcpath, dstpath):
"""
srcpath: result files before merge and nms.txt的信息格式为:[P0770__1__0___0 confidence poly]
dstpath: result files after merge and nms.保存的txt信息格式为:[P0770 confidence poly]
"""
# srcpath = r'/home/dingjian/evaluation_task1/result/faster-rcnn-59/comp4_test_results'
# dstpath = r'/home/dingjian/evaluation_task1/result/faster-rcnn-59/testtime'
# mergebase(srcpath,
# dstpath,
# py_cpu_nms_poly)
mergebase_parallel(srcpath,
dstpath,
py_cpu_nms_poly_fast)
if __name__ == '__main__':
mergebypoly(r'ResultMerge_example', r'ResultMerge_example_result')
# mergebyrec()