def label_process(detect_result, iou_thresh, iou_thresh11):
assert detect_result != ''
x_center, y_center = detect_result[1::6], detect_result[2::6]
w_center, h_center = detect_result[3::6], detect_result[4::6]
detect_result[1::6] = [i - 0.5 * j for i, j in zip(x_center, w_center)]
detect_result[2::6] = [i - 0.5 * j for i, j in zip(y_center, h_center)]
detect_result[3::6] = [i + 0.5 * j for i, j in zip(x_center, w_center)]
detect_result[4::6] = [i + 0.5 * j for i, j in zip(y_center, h_center)]
list_new = []
for label_values in np.unique(detect_result[::6]):
list_values = np.array([
detect_result[6 * idx:6 * idx + 6]
for idx, i in enumerate(detect_result[::6]) if i == label_values
])
boxes = list_values[:, 1:5].tolist()
scores = list_values[:, 5].tolist()
labels = list_values[:, 0].tolist()
if label_values in [2, 11]:
boxes, scores, labels = nms([boxes], [scores], [labels],
weights=None,
iou_thr=iou_thresh11)
else:
boxes, scores, labels = nms([boxes], [scores], [labels],
weights=None,
iou_thr=iou_thresh)
for box in list_values:
if box[-1] in scores:
list_new.extend(box)
return list_new
def ensemble_models(ipt_json_paths, opt_json_path, img_ann_path, weights, method='weighted_boxes_fusion', iou_thr=0.3,
skip_box_thr=0.0001,
sigma=0.1):
img_info_dicts = mmcv.load(img_ann_path)['images']
img_info_dict = dict()
for img_info in img_info_dicts:
img_info_dict[img_info['id']] = img_info
res_dicts = []
res_dict = dict()
for json_path in ipt_json_paths:
res_dicts.append(json_to_lisdict(json_path, img_info_dict))
for img_id in res_dicts[0]:
boxes_list = []
scores_list = []
labels_list = []
for i in range(len(res_dicts)):
if img_id not in res_dicts[i]:
boxes_list.append([])
scores_list.append([])
labels_list.append([])
else:
boxes_list.append(res_dicts[i][img_id]['boxes'])
scores_list.append(res_dicts[i][img_id]['scores'])
labels_list.append(res_dicts[i][img_id]['labels'])
if method == 'nms':
boxes, scores, labels = nms(boxes_list, scores_list, labels_list, weights=weights, iou_thr=iou_thr)
elif method == 'soft_nms':
boxes, scores, labels = soft_nms(boxes_list, scores_list, labels_list, weights=weights, iou_thr=iou_thr,
sigma=sigma, thresh=skip_box_thr)
elif method == 'non_maximum_weighted':
boxes, scores, labels = non_maximum_weighted(boxes_list, scores_list, labels_list, weights=weights,
iou_thr=iou_thr,
skip_box_thr=skip_box_thr)
else:
boxes, scores, labels = weighted_boxes_fusion(boxes_list, scores_list, labels_list, weights=weights,
iou_thr=iou_thr,
skip_box_thr=skip_box_thr)
res_dict[img_id] = dict(boxes=boxes, scores=scores, labels=labels)
lisdict_to_json(res_dict, opt_json_path, img_info_dict)
def ensemble_multibox(boxes, scores, labels, iou_thr, sigma,
skip_box_thr, weights=None, method='wbf'):
if method=='nms':
boxes, scores, labels = nms(boxes, scores, labels,
weights=weights,
iou_thr=iou_thr)
elif method=='soft_nms':
boxes, scores, labels = soft_nms(boxes, scores, labels,
weights=weights,
sigma=sigma,
iou_thr=iou_thr,
thresh=skip_box_thr)
elif method=='nms_weight':
boxes, scores, labels = non_maximum_weighted(boxes, scores, labels,
weights=weights,
iou_thr=iou_thr,
skip_box_thr=skip_box_thr)
elif method=='wbf':
boxes, scores, labels = weighted_boxes_fusion(boxes, scores, labels,
weights=weights,
iou_thr=iou_thr,
skip_box_thr=skip_box_thr)
return boxes, scores, labels
def mergeResults(self,outfile,merge_input_mode="xywh",is_nms=True,nms_thresh=0.9,nms_name="nms"):
"""
:param is_nms: do non-maximum suppression on after merge
:param nms_thresh: non-maximum suppression IoU threshold
:return:
"""
print('Loading source annotation json file: {}'.format(self.srcannopath))
with open(self.srcannopath, 'r') as load_f:
srcanno = json.load(load_f)
mergedresults = defaultdict(list)
# random.seed(0)
# print("len",len(self.results))
keep_input=[]
for (filename, objlist) in self.results.items():
# for (filename, objlist) in random.sample(self.results.items(),2):
# srcfile, scale, left, up = filename.split('___')
# srcfile =srcfile.replace('_IMG', '/IMG')+".jpg"
# up =up[:-4]
# # print(filename, objlist)
# # srcimageid =srcfile[-2:]
# # print(srcfile)
# srcimageid = srcanno[srcfile]['image id']
# print("srcimageid",srcimageid)
# print(srcfile, scale, left, up )
srcfile, paras = filename.split('___')#srcfile, paras 15_Nanshani_Park_IMG_15_04 0.5__4224__6144.jpg
# print("srcfile, paras",srcfile, paras )
srcfile = srcfile.replace('_IMG', '/IMG') + self.imgext#02_Xili_Crossroad_IMG_02_01___0.5__0__0.jpg
srcimageid = srcanno[srcfile]['image id']
scale, left, up = paras.replace(self.imgext, '').split('__')#scale, left, up 0.5 4224 6144
print(srcfile, scale, left, up )
print(f"before objlist {len(objlist)}")
if not iskeep_dets:
for objdict in objlist:
mergedresults[srcimageid].append([*recttransfer(objdict['bbox'], float(scale), int(left), int(up),merge_input_mode),objdict['score'], objdict['category_id'],objdict['image_id']])
if iskeep_dets:
keep_input=keep_input+[[srcimageid,int(left), int(up),float(scale),i['bbox'][0],i['bbox'][1],i['bbox'][2],i['bbox'][3],i['score'],i['image_id'],i['category_id']] for i in objlist]
# keep_input.append([[srcimageid,int(left), int(up),float(scale),i['bbox'][0],i['bbox'][1],i['bbox'][2],i['bbox'][3],i['score'],i['image_id'],i['category_id']] for i in objlist])
if iskeep_dets:
print(f"before keep {len(keep_input)}")
if 391<=srcimageid<=420:#14otcUP_boundary
keep_dets,_keep_values=self.keep_dets(np.array(keep_input),UP_boundary[0],PANDA_TEST_SIZE[0])
if 421<=srcimageid<=450:#15 nanshangongyuan
keep_dets,_keep_values=self.keep_dets(np.array(keep_input),UP_boundary[1],PANDA_TEST_SIZE[1])
if 451<=srcimageid<=465:#16xiaoxue----------01
keep_dets,_keep_values=self.keep_dets(np.array(keep_input),UP_boundary[2],PANDA_TEST_SIZE[2])
if 466<=srcimageid<=480:#16xiaoxue--------02
keep_dets,_keep_values=self.keep_dets(np.array(keep_input),UP_boundary[3],PANDA_TEST_SIZE[2])
if 481<=srcimageid<=510:#17zhongguan
keep_dets,_keep_values=self.keep_dets(np.array(keep_input),UP_boundary[4],PANDA_TEST_SIZE[3])
if 511<=srcimageid<=540:#18xilin-------01
keep_dets,_keep_values=self.keep_dets(np.array(keep_input),UP_boundary[5],PANDA_TEST_SIZE[4])
if 541<=srcimageid<=555:#18xilin----------02
keep_dets,_keep_values=self.keep_dets(np.array(keep_input),UP_boundary[6],PANDA_TEST_SIZE[5])
print(f"after keep {len(keep_dets)}")
for objdict,keep_value in zip(keep_dets,_keep_values):
left, up,scale=keep_value[0],keep_value[1],keep_value[2]
# print("objdict",objdict)#{'image_id': 7110, 'bbox': [47.7, 866.2, 198.8, 442.8], 'score': 0.83231, 'category_id': 1}
mergedresults[srcimageid].append([*recttransfer(objdict['bbox'], float(scale), int(left), int(up),merge_input_mode),
objdict['score'], objdict['category_id'],objdict['image_id']])
img_size = {}
for anno in srcanno:
# print(srcanno[anno]['image id'])
img_size[srcanno[anno]['image id']] = srcanno[anno]['image size']
if is_nms:
if nms_name=="nms":
for (imageid, objlist) in mergedresults.items():
masxlist=[i[2]*i[3] for i in objlist]
max_wh=np.max(masxlist)
objlist=[[i[0],i[1],i[2],i[3],i[4]*0.05+i[3]*i[2]*0.95/max_wh,i[5],i[6]] for i in objlist ]
keep = py_cpu_nms(np.array(objlist), nms_thresh)
outdets = []
for index in keep:
outdets.append(objlist[index])
mergedresults[imageid] = outdets
if nms_name=="setnms":
for (imageid, objlist) in mergedresults.items():
print("input nms element",objlist[0])#[829, 5939, 923, 6000, 0.24672751128673553, 1, 149]
print(f"before setnms {nms_thresh} ",len(objlist))
keep=np.array(objlist)[set_cpu_nms(np.array(objlist), nms_thresh)].tolist()
# print("keep",keep,"\n",len(keep),type(keep))
print(f"{imageid} after setnms_{nms_thresh} ",len(keep))
mergedresults[imageid] = keep
if nms_name=="emnms":
for (imageid, objlist) in mergedresults.items():
size_anno = img_size[imageid]
boxes = [[obj[0] / size_anno['width'], obj[1] / size_anno['height'],
obj[2] / size_anno['width'], obj[3] / size_anno['height']] for obj in objlist]
scores = [obj[4] for obj in objlist]
labels = [obj[5] for obj in objlist]
boxes, scores, labels = nms([boxes], [scores], [labels])
boxes[:, [0, 2]] *= size_anno['width']
boxes[:, [1, 3]] *= size_anno['height']
outdets = [x[0] + [x[1], x[2]] for x in zip(boxes.tolist(), scores.tolist(), labels.tolist())]
mergedresults[imageid] = outdets
if nms_name=="softnms":
for (imageid, objlist) in mergedresults.items():
print(f"{imageid} before softnms_{nms_thresh} ",len(objlist))
# print("ssss",len(objlist[0]))
# print("ssss",objlist[0])
masxlist=[i[2]*i[3] for i in objlist]
max_wh=np.max(masxlist)
objlist=[[i[0],i[1],i[2],i[3],i[4]*0.05+i[3]*i[2]*0.95/max_wh,i[5],i[6]] for i in objlist ]
# tempmax=np.max(np.array(objlist)[:, 4])
# print("max",tempmax)#208909381.05317593
# objlist=[[i[0],i[1],i[2],i[3],i[4]/(tempmax+0.00001),i[5],i[6]] for i in objlist ]
# print(objlist)
newdets,keep=soft_nms(np.array(objlist),iou_thr=nms_thresh, method='linear',sigma=0.5, min_score=1e-3)#'gaussian''linear',
# keep =py_cpu_softnms(np.array(objlist),thresh=nms_thresh, Nt=0.02, sigma=0.5, method=1)
# print(keep)
outdets = []
for index in keep:
outdets.append(objlist[index])
print(f"{imageid} after softnms_{nms_thresh} ",len(keep))
mergedresults[imageid] = outdets
savelist = []
def say2(iss):
imageid, objlist=iss[0],iss[1]
# print(imageid, objlist)
templist=[]
for obj in objlist:#obj [22528, 1270, 24576, 1, 1.0, 4]
# print(obj)
templist.append({
"image_id": imageid,
"category_id": obj[5],
"bbox": tlbr2tlwh(obj[:4]),
"score": obj[4]
})
if test:
print(f"fliter berfore len {len(templist)}")
if isfliter:
if 391<=imageid<=420:#14otc
templist=fliter(templist,fliterscore["14_OCT"],AnotPath="/root/data/gvision/dataset/xml/14_OCT_Habour.xml",
segma_woh=3,segma_area=3,up_bound=4000,down_bound=None,down_fs=0.95,yichang=0)
if 421<=imageid<=450:#15 nanshangongyuan
templist=fliter(templist,fliterscore["15_nanshan"],AnotPath="/root/data/gvision/dataset/xml/15_Nanshani_Park.xml",
segma_woh=3,segma_area=2,up_bound=1500,down_bound=7000,down_fs=None,yichang=0)
if 451<=imageid<=465:#16xiaoxue----------01
templist=fliter(templist,fliterscore["1601_shool"],AnotPath="/root/data/gvision/dataset/xml/IMG_16_01_head.xml",
segma_woh=3,segma_area=3,up_bound=0,down_bound=None,down_fs=None,yichang=0)
if 466<=imageid<=480:#16xiaoxue--------02
templist=fliter(templist,fliterscore["1602_shool"],AnotPath="/root/data/gvision/dataset/xml/IMG_16_25_02_.xml",
segma_woh=3,segma_area=3,up_bound=0,down_bound=None,down_fs=None,yichang=0)
if 481<=imageid<=510:#17zhongguan
templist=fliter(templist,fliterscore["17_newzhongguan"],AnotPath="/root/data/gvision/dataset/xml/17_New_Zhongguan.xml",
segma_woh=3,segma_area=3,up_bound=6000,down_bound=7000,down_fs=None,yichang=0)
if 511<=imageid<=540:#18xilin-------01
templist=fliter(templist,fliterscore["1801_xilin"],AnotPath="/root/data/gvision/dataset/xml/IMG_18_01_01.xml",
segma_woh=3,segma_area=3,up_bound=4000,down_bound=None,down_fs=None,yichang=0)
if 541<=imageid<=555:#18xilin----------02
templist=fliter(templist,fliterscore["1802_xilin"],AnotPath="/root/data/gvision/dataset/xml/IMG_18_02.xml",
segma_woh=3,segma_area=3,up_bound=4000,down_bound=None,down_fs=None,yichang=0)
if isdel_inter:
templist=del_inter(templist)
if test:
print(f"del_inter after len {len(templist)}")
return templist
executor = ThreadPoolExecutor(max_workers=80)
func_var = [[file_name,dict_value] for file_name,dict_value in mergedresults.items()]
print("merge bbox into self'image start ")
pbar2= tqdm(total=len(mergedresults), ncols=50)
for temp in executor.map(say2,func_var):
savelist+=temp
pbar2.update(1)
pbar2.close()
with open(os.path.join(self.outpath, outfile), 'w', encoding=self.code) as f:
dict_str = json.dumps(savelist, indent=2)
f.write(dict_str)
print(f"save ***results*** json :{os.path.join(self.outpath, outfile)}")