%\setlength{\tabcolsep}{0.5pt}
\begin{tabular}{c|c|c|c|c|c|c|c}
\hline
\textit{Difficulty mode} & \textit{Methods} & \textit{cAcc} ($\uparrow$) & \textit{ACD} ($\downarrow$) & \textit{mCCD} ($\downarrow$) & \textit{mCIoU} ($\uparrow$) & \textit{mAP50} ($\uparrow$) & \textit{mmAP} ($\uparrow$) \\
\hline
\multirow{4}{*}{Easy} REPLACE_easy \hline
\multirow{4}{*}{Medium} REPLACE_medium \hline
\multirow{4}{*}{Hard} REPLACE_hard \hline
\multirow{5}{*}{Averaged} REPLACE_averaged \hline
\end{tabular}
\end{table*}
'''
from boxx import *
from boxx import loadData, dicto, openwrite
toMethodName = dicto(mix='SR (ours)',
only_gan='SR w/o S (ours)',
no_gan='SR w/o R (ours)',
single_fpn='Baseline')
def getLatexMethodName(myName):
for k, v in toMethodName.items():
if myName.startswith(k):
return v
return myName
methodOrder = ['single_fpn', 'no_gan', 'only_gan', 'mix']
evalOrder = [
'Difficulty mode', 'Methods', 'cAcc', 'ACD', 'mCCD', 'mCIoU', 'mAP50',
'mmAP'
]
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ @author: DIYer22@github @mail: [email protected] Created on Thu Dec 27 22:07:37 2018 """ from boxx import dicto config = dicto({ "debug": False, "ROUND_NUM": 2, "column_names": ['level', 'method', 'cAcc', 'mCIoU', 'ACD', 'mCCD', 'mAP50', 'mmAP'] }) if __name__ == "__main__": pass
def visBboxList(rgb,
bboxList,
path='/tmp/visCanvas/tmp.pdf',
classNames=None,
box_alpha=0.8,
show_class=True,
thresh=0.1,
show_mask=None,
pltshow=False):
if classNames is None:
classNames = {i: "%d-class" % i for i in range(1111)}
classn = len(classNames)
dataset = dicto(classes=classNames)
cls_segms = [[] for _ in range(classn)]
cls_boxes = [np.zeros((0, 5), np.float32) for _ in range(classn)]
#cls_segms = None
#cls_boxes = [np.zeros((0,5), np.float32) for _ in range(classn)]
bboxnps = bboxList.bbox
extraFields = {
k: v.cpu().numpy()
for k, v in bboxList.extra_fields.items()
}
if show_mask is None:
if 'mask' in extraFields:
show_mask = True
for ind, bboxnp in enumerate(bboxnps):
# g()
other = dicto({k: v[ind] for k, v in extraFields.items()})
if other.scores < thresh:
continue
c = other.labels
if show_mask:
rle = mask2rle(other.mask)
cls_segms[c].append(rle)
if bboxList.mode == 'xyxy':
cls_boxes[c] = np.append(cls_boxes[c],
[list(bboxnp) + [other.scores]], 0)
cls_keyps = None
if not show_mask:
cls_segms = None
# g()
outputDir, name = dirname(path), filename(path)
vis_one_image(
rgb, # BGR -> RGB for visualization
name,
outputDir,
cls_boxes,
cls_segms,
cls_keyps,
dataset=dataset,
box_alpha=0.8,
show_class=True,
thresh=thresh,
kp_thresh=2,
pltshow=pltshow,
)
def forward(self, feats, xyens):
logName = 'cyc_r: %s, out_cyc_r: %s' % (self.cyc_r, self.out_cyc_r
or 'N')
logTag = timegap(self.log_freq, logName)
if logTag:
logDic = dicto()
if self.layerNorma:
feats = layerNormaFun(feats)
tensorType = feats.type()
shape = self.shape = feats.shape
feats = feats.view(-1, *shape[-2:])
xyens = xyens.view(-1, 3)
pgts = xyens[..., [1, 0]].cpu().numpy()
existMask = xyens[..., -1].type(tensorType)
# with timeit(logName):
masks = map2(getMaskOfPgt, [
dict(pgt=pgt,
cycle_tmpl=self.cycle_tmpl,
shape=shape,
out_cyc_r=self.out_cyc_r) for pgt in pgts
])
# masks = mapmp(self.getMask, pgts, pool=4)
masks = np.array(masks)
masks = th.from_numpy(np.uint8(masks)).type(tensorType).cuda()
loss = 0
#(lambda a,b,t=1:e**(t*a)/(e**(t*a)+e**(t*b)))(2,1,5)
def softmaxFgBgOld(fg, bg, t=1):
fge = th.exp(fg * t)
bge = th.exp(bg * t)
prob = fge / (fge + bge + eps)
return prob
def softmaxFgBgSubMax(fg, bg, t=1):
fg = fg * t
bg = bg * t
maxx = max(float(fg.max()), float(bg.max()))
fge = th.exp(fg - maxx)
bge = th.exp(bg - maxx)
prob = fge / (fge + bge + eps)
return prob
def softmaxFgBgSub(fg, bg, t=1):
diff = bg - fg
toExp = t * diff
if (toExp > 80).sum() and timegap(1, 'toExp'):
from boxx import prettyFrameLocation, pred
print(prettyFrameLocation())
pred - "toExp.max() is %.2f > 80, diff.max() is %.2f" % (
toExp.max(), diff.max())
prob = 1 / (1 + th.exp(toExp))
return prob
softmaxFgBg = softmaxFgBgSubMax
def CE(fg, bg):
prob = softmaxFgBg(fg, bg)
avgLosses = -th.log(prob + eps)
return avgLosses
if 'avg' in self.poolings:
bgAvgPool = (feats * masks[..., 0, :, :]).sum(-1).sum(-1) / (
masks[..., 0, :, :].sum(-1).sum(-1) + eps)
fgAvgPool = (feats * masks[..., 1, :, :]).sum(-1).sum(-1) / (
masks[..., 1, :, :].sum(-1).sum(-1) + eps)
avgProbs = softmaxFgBg(fgAvgPool, bgAvgPool, self.temper)
avgLosses = -th.log(avgProbs + eps)
indexMask = existMask * (avgProbs < self.probMargin).type(
tensorType) if self.probMargin else existMask
avgLoss = (avgLosses * indexMask).sum() / (indexMask.sum() + eps)
loss += avgLoss
if logTag:
logDic.avgLoss = float(avgLoss)
logDic.avgProb = float(avgProbs.mean())
if 'max' in self.poolings:
bgMaxPool = (feats * masks[..., 0, :, :]).max(-1)[0].max(-1)[0]
fgMaxPool = (feats * masks[..., 1, :, :]).max(-1)[0].max(-1)[0]
maxProbs = softmaxFgBg(fgMaxPool, bgMaxPool, self.temper)
maxLosses = -th.log(maxProbs + eps)
indexMask = existMask * (maxProbs < self.probMargin).type(
tensorType) if self.probMargin else existMask
maxLoss = (maxLosses * indexMask).sum() / (indexMask.sum() + eps)
loss += maxLoss
if logTag:
logDic.maxLoss = float(maxLoss)
logDic.maxProb = float(maxProbs.mean())
if logTag:
print("%s | %s" % (logName, ', '.join(
map(lambda kv: "%s: %.3f" % kv, logDic.items()))))
# print(Markdown([{k:strnum(v) for k,v in logDic.items()}]))
# g()
return loss
classNames = dicto(
enumerate([
'__background__', '上好佳荷兰豆55g', '菜园小饼80g', '上好佳鲜虾片40g', '上好佳蟹味逸族40g',
'妙脆角魔力炭烧味65g', '盼盼烧烤牛排味块105g', '上好佳鲜虾条40g', '上好佳洋葱圈40g',
'上好佳日式鱼果海苔味50g', '奇多日式牛排味90g', '奇多美式火鸡味90g', '上好佳粟米条草莓味40g',
'甘源蟹黄味瓜子仁75g', '惠宜开心果140g', '惠宜咸味花生350g', '惠宜腰果160g', '惠宜枸杞100g',
'惠宜地瓜干228g', '惠宜泰国芒果干80g', '惠宜黄桃果干75g', '惠宜柠檬片65g', '新疆和田滩枣454g',
'惠宜香菇100g', '惠宜桂圆干500g', '惠宜茶树菇200g', '豪雄单片黑木耳150g', '惠宜煮花生454g',
'惠宜黄花菜100g', '洽洽凉茶瓜子150g', '洽洽奶香味瓜子150g', '车仔茶包绿茶50g', '车仔茶包红茶50g',
'优乐美香芋味80g', '优乐美红豆奶茶65g', '欢泥冲调土豆粥25g', '江中猴姑早餐米稀40g', '永和豆浆甜豆浆粉210g',
'立顿柠檬风味茶180g', '桂格多种莓果麦片40g', '荣怡谷麦加黑米味30g', '荣怡谷麦加红豆味30g',
'今野香辣牛肉面112g', '今野老坛酸菜牛肉面118g', '今野红烧牛肉面114g', '合味道海鲜风味84g',
'康师傅白胡椒肉骨面76g', '康师傅香辣牛肉面105g', '康师傅香辣蒜味排骨面108g', '康师傅藤椒牛肉面82g',
'华丰鸡肉三鲜伊面87g', '康师傅黑胡椒牛排面104g', '五谷道场红烧牛肉面100g', '康师傅老坛酸菜牛肉面114g',
'Aji泡芙饼干芒果菠萝味60g', '庆联蓝莓味夹心饼63g', '庆联凤梨味夹心饼63g', '庆联草莓味夹心饼63g',
'嘉顿威化饼干草莓味50g', '嘉顿威化饼干柠檬味50g', '爱时乐香草牛奶味50g', '爱时乐巧克力味50g',
'百力滋海苔味60g', '百力滋草莓牛奶味45g', '雀巢脆脆鲨80g', '纳宝帝巧克力味威化58g',
'桂力地中海风味面包条50g', '康师傅妙芙巧克力味48g', '爱乡亲唱片面包90g', '达利园派草莓味单个装*',
'mini奥利奥55g', '农夫山泉矿泉水550ml', '怡宝矿泉水555ml', '可口可乐零度500ml', '可口可乐500ml',
'百事可乐600ml', '芬达苹果味500ml', '芬达橙味500ml', '雪碧500ml', '喜力啤酒500ml',
'百威啤酒600ml', '百事可乐330ml', '可口可乐330ml', '王老吉310ml', '茶派柚子绿茶500ml',
'茶派玫瑰荔枝红茶500ml', '康师傅冰红茶250ml', '加多宝250ml', 'RIO果酒水蜜桃味275ml',
'RIO果酒蓝玫瑰威士忌味275ml', '牛栏山二锅头100ml', '哈尔滨啤酒330ml', '青岛啤酒330ml',
'雪花啤酒330ml', '哈尔滨啤酒500ml', 'KELER啤酒500ml', '百威啤酒500ml', 'QQ星全聪奶125ml',
'QQ星均膳奶125ml', '娃哈哈AD钙奶220g', '活力宝动力源105ml', '旺仔牛奶复原乳250ml',
'伊利纯牛奶250ml', '维他低糖原味豆奶250ml', '百怡花生牛奶250ml', '惠宜原味豆奶250ml',
'伊利优酸乳250ml', '伊利早餐奶250ml', '达利园桂圆莲子360g', '银鹭冰糖百合银耳280g',
'喜多多什锦椰果567g', '都乐菠萝块567g', '都乐菠萝块234g', '银鹭薏仁红豆粥280g', '银鹭莲子玉米粥280g',
'银鹭紫薯紫米粥280g', '银鹭椰奶燕麦粥280g', '银鹭黑糖桂圆280g', '梅林午餐肉340g', '珠江桥牌豆豉鱼150g',
'古龙原味黄花鱼120g', '雄鸡标椰浆140ml', '德芙芒果酸奶巧克力42g', '德芙摩卡巴旦木巧克力43g',
'德芙百香果白巧克力42g', 'MM花生牛奶巧克力豆40g', 'MM牛奶巧克力豆40g', '好时牛奶巧克力40g',
'好时曲奇奶香白巧克力40g', '脆香米海苔白巧克力24g', '脆香米奶香白巧克力24g', '士力架花生夹心巧克力51g',
'士力架燕麦花生夹心巧克力40g', '士力架辣花生夹心巧克力40g', '炫迈果味浪薄荷味37g', '炫迈果味浪柠檬味37g',
'炫迈薄荷味21g', '炫迈葡萄味21g', '炫迈西瓜味21g', '炫迈葡萄味50g', '绿箭无糖薄荷糖茉莉花茶味34g',
'绿箭5片装15g', '比巴卜棉花泡泡糖可乐味11g', '比巴卜棉花泡泡堂葡萄味11g', '星爆缤纷原果味25g',
'阿尔卑斯焦香牛奶味硬糖45g', '阿尔卑斯牛奶软糖黄桃酸奶味47g', '阿尔卑斯牛奶软糖蓝莓酸奶味47g', '王老吉润喉糖28g',
'伊利牛奶片蓝莓味32g', '熊博士口嚼糖草莓牛奶味52g', '彩虹糖原果味45g', '宝鼎天鱼陈酿米醋245ml',
'恒顺香醋340ml', '太太乐鸡精200g', '家乐香菇鸡茸汤料41g', '惠宜辣椒粉15g', '惠宜生姜粉15g',
'味好美椒盐20g', '海星加碘精制盐400g', '恒顺料酒500ml', '东古味极鲜酱油150ml', '东古一品鲜酱油150ml',
'欣和六月鲜酱油160ml', '李施德林零度漱口水80ml', '舒肤佳纯白清香沐浴露100ml', '美涛定型啫喱水60ml',
'清扬男士洗发露活力运动薄荷型50ml', '蓝月亮风清白兰洗衣液80g', '高露洁亮白小苏打180g', '高露洁冰爽180g',
'舒亮皓齿白80g', '云南白药牙膏45g', '舒克宝贝儿童牙刷', '清风原木纯品金装100x3', '洁柔face150x3',
'斑布100x3', '维达婴儿150x3', '相印小黄人150x3', '清风原木纯品黑耀150x3', '洁云绒触感130x3',
'舒洁萌印花120x2', '相印红悦130x3', '得宝苹果木味90x4', '清风新韧纯品130x3', '金鱼竹浆绿135x3',
'清风原木纯品150x2', '洁柔face130x3', '维达立体美110x3', '洁柔CS单包*', '相印小黄人单包*',
'清风原色单包*', '相印茶语单包*', '清风质感纯品单包*', '米奇1928笔记本', '广博固体胶15g', '票据文件袋',
'晨光蜗牛改正带', '鸿泰液体胶50g', '马培德自粘性标签', '东亚记号笔'
]))