def ann(self, iid):
ann_path = self.ann_path.format(iid=iid)
scale = self.scales.get(iid, None)
if not os.path.exists(ann_path):
ann_path = None
return None, iid
else:
return Ann(file=ann_path, scale=scale), iid
def fun(timg):
img, tgt = timg.ssd()
if cuda: img = img.cuda()
dets = model.forward(Variable(img))
dim = img.size(2)
dets = dets[0].data
if cuda: dets = dets.cpu()
ann = Ann(tensor=dets, dim=img.size(2))
return ann
def merge(self, fun, d=900, s=800, mimg=None):
ret = []
for timg, x, y in self.mtile(mimg, d, s):
ann = fun(timg)
if ann is None: continue
ann.dxy(-x, -y)
ret.append(ann.dets)
ret = np.concatenate(ret)
return Ann(dets=ret)
def posmid(self, d, dist=None):
if dist is None: dist = 1.5 * d
pos = list([aimg.np() for cl, aimg in self.crop_ann(d)])
dets, _ = self.ann.midd(dist)
ann = Ann(dets=dets)
print("posmid", len(pos), ann.count)
aimg = AnnImg(self.img, ann)
mid = list([aimg.np() for cl, aimg in aimg.crop_ann(d)])
Xp, Xn = np.stack(pos), np.stack(mid)
Yp, Yn = np.ones(Xp.shape[0]), np.zeros(Xn.shape[0])
return np.concatenate([Xp, Xn]), np.concatenate([Yp, Yn]), Xp, Xn
def neg(self, ratio=1.0, num=None, minn=None):
if num is None: num = int(self.count * ratio)
if minn is not None: num = max(num, minn)
mask = self.neg_mask().inv().np()
#print("mask", mask.shape)
y, x = mask[0].nonzero()
pts = np.stack([x, y], axis=1)
np.random.shuffle(pts)
xy = pts[:num]
cl = -1 * np.ones((xy.shape[0], 1))
ann = Ann(dets=np.concatenate([cl, xy], axis=1).astype('int32'))
return self.wann(ann)
def nimg(self, d, ratio=1):
numneg = int(self.count * ratio)
W, H = self.WH
arr = []
steps = 0
while len(arr) < numneg and steps < 10000:
steps += 1
x, y = (randint(0, W), randint(0, H))
if self.cropdd(x, y, d).count == 0:
arr.append((-1, x, y))
ann = Ann(dets=np.array(arr))
return AnnImg(self.img, ann)
def __init__(self, img=None, ann=None, **kwargs):
if not img is None:
self.img = img
elif "npimg" in kwargs:
self.img = Image.fromarray(kwargs["npimg"].astype('uint8'))
else:
self.img = Image.open(kwargs["img_path"])
if ann is not None: self.ann = ann
elif "ann_path" in kwargs:
scale = kwargs.get("scale", None)
self.sc = scale
#print("AnnImg scale", scale)
self.ann = Ann(file=kwargs["ann_path"], scale=scale)
else:
self.ann = None
def hneg(self, ratio=1.0, num=None, minn=None, th=False, conf=10):
if num is None: num = int(self.count * ratio)
if minn is not None: num = max(num, minn)
mask = self.neg_mask().inv().np()
#print("mask", mask.shape)
y, x = mask[0].nonzero()
hm = self.np()[0]
#print("hm", hm.shape)
idx = np.argsort(hm[y, x])
py, px = y[idx], x[idx]
xy = np.stack([px, py], axis=1)
cl = -1 * np.ones((xy.shape[0], 1))
h = hm[xy[:, 1], xy[:, 0]]
ann = Ann(dets=np.concatenate([cl.reshape(-1, 1), xy], axis=1).astype(
'int32'))
ann.conf = ((255 - h) * 100) / 255
ann = ann.fconf(conf)
#print(ann)
if ann.count < num: return self.wann(ann)
if th: ann = ann.pnms(50)
return self.wann(ann.take(num))
def open(cls, img_path, ann_path=None, scale=None):
ann = None
if not ann_path is None:
ann = Ann(file=ann_path, scale=scale)
return AnnImg(img, ann)