分类: Python/Ruby
2022-04-26 17:38:17
mulpicplus = "3" #1 for normal,2 for 4pic plus,3 for 9pic plus and so on
assert(int(mulpicplus)>=1)
if mulpicplus == "1":
pred = model(img,
augment=augment,
visualize=increment_path(save_dir / Path(path).stem, mkdir=True) if visualize else False)[0]
else:
xsz = img.shape[2]
ysz = img.shape[3]
mulpicplus = int(mulpicplus)
x_smalloccur = int(xsz / mulpicplus * 1.2)
y_smalloccur = int(ysz / mulpicplus * 1.2)
for i in range(mulpicplus):
x_startpoint = int(i * (xsz / mulpicplus))
for j in range(mulpicplus):
y_startpoint = int(j * (ysz / mulpicplus))
x_real = min(x_startpoint + x_smalloccur, xsz)
y_real = min(y_startpoint + y_smalloccur, ysz)
if (x_real - x_startpoint) % 64 != 0:
x_real =外汇跟单gendan5.com x_real - (x_real-x_startpoint) % 64
if (y_real - y_startpoint) % 64 != 0:
y_real = y_real - (y_real - y_startpoint) % 64
dicsrc = img[:, :, x_startpoint:x_real,
y_startpoint:y_real]
pred_temp = model(dicsrc,
augment=augment,
visualize=increment_path(save_dir / Path(path).stem, mkdir=True) if visualize else False)[0]
pred_temp[..., 0] = pred_temp[..., 0] + y_startpoint
pred_temp[..., 1] = pred_temp[..., 1] + x_startpoint
if i==0 and j == 0:
pred = pred_temp
else:
pred = torch.cat([pred, pred_temp], dim=1)
# Apply NMS
pred = non_max_suppression(pred, conf_thres, iou_thres, classes, agnostic_nms, max_det=max_det)