import?torch
import?torch.backends.cudnn?as?cudnn
from?data?import?COLORS
from?data?import?cfg?set_cfg
from?yolact?import?Yolact
from?utils.augmentations?import?FastbaseTransform
from?utils?import?timer
from?utils.functions?import?SavePath
from?layers.output_utils?import?postprocess?undo_image_transformation
import?cv2?as?cv
from?collections?import?defaultdict

#?參數配置

score_threshold?=?0.15
top_k?=?15
display_masks?=?True
display_text?=?True
display_bboxes?=?True
display_scores?=?True

#?全局變量
iou_thresholds?=?[x?/?100?for?x?in?range（50?100?5）]
coco_cats?=?{}??#?Call?prep_coco_cats?to?fill?this
coco_cats_inv?=?{}
color_cache?=?defaultdict（lambda:?{}）


def?prep_display（dets_out?img?h?w?undo_transform=True?class_color=False?mask_alpha=0.45?fps_str=‘‘）:
????“““
????Note:?If?undo_transform=False?then?im_h?and?im_w?are?allowed?to?be?None.
????“““
????if?undo_transform:
????????img_numpy?=?undo_image_transformation（img?w?h）
????????img_gpu?=?torch.Tensor（img_numpy）.cuda（）
????else:
????????img_gpu?=?img?/?255.0
????????h?w?_?=?img.shape

????with?timer.env（‘Postprocess‘）:
????????t?=?postprocess（dets_out?w?h?visualize_lincomb=False
????????????????????????crop_masks=True
????????????????????????score_threshold=score_threshold）
????????torch.cuda.synchronize（）

????with?timer.env（‘Copy‘）:
????????if?cfg.eval_mask_branch:
????????????#?Masks?are?drawn?on?the?GPU?so?don‘t?copy
????????????masks?=?t[3][:top_k]
????????classes?scores?boxes?=?[x[:top_k].cpu（）.numpy（）?for?x?in?t[:3]]

????num_dets_to_consider?=?min（top_k?classes.shape[0]）
????for?j?in?range（num_dets_to_consider）:
????????if?scores[j]?????????????num_dets_to_consider?=?j
????????????break

????#?Quick?and?dirty?lambda?for?selecting?the?color?for?a?particular?index
????#?Also?keeps?track?of?a?per-gpu?color?cache?for?maximum?speed
????def?get_color（j?on_gpu=None）:
????????global?color_cache
????????color_idx?=?（classes[j]?*?5?if?class_color?else?j?*?5）?%?len（COLORS）

????????if?on_gpu?is?not?None?and?color_idx?in?color_cache[on_gpu]:
????????????return?color_cache[on_gpu][color_idx]
????????else:
????????????color?=?COLORS[color_idx]
????????????if?not?undo_transform:
????????????????#?The?image?might?come?in?as?RGB?or?BRG?depending
????????????????color?=?（color[2]?color[1]?color[0]）
????????????if?on_gpu?is?not?None:
????????????????color?=?torch.Tensor（color）.to（on_gpu）.float（）?/?255.
????????????????color_cache[on_gpu][color_idx]?=?color
????????????return?color

????#?First?draw?the?masks?on?the?GPU?where?we?can?do?it?really?fast
????#?Beware:?very?fast?but?possibly?unintelligible?mask-drawing?code?ahead
????#?I?wish?I?had?access?to?OpenGL?or?Vulkan?but?alas?I?guess?Pytorch?tensor?operations?will?have?to?suffice
????#?After?this?mask?is?of?size?[num_dets?h?w?1]
????if?display_masks?and?cfg.eval_mask_branch?and?num_dets_to_consider?>?0:
????????masks?=?masks[: