NPU人体检测
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176
py_utils/coco_utils.py
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176
py_utils/coco_utils.py
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from copy import copy
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import os
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import cv2
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import numpy as np
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import json
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class Letter_Box_Info():
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def __init__(self, shape, new_shape, w_ratio, h_ratio, dw, dh, pad_color) -> None:
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self.origin_shape = shape
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self.new_shape = new_shape
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self.w_ratio = w_ratio
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self.h_ratio = h_ratio
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self.dw = dw
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self.dh = dh
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self.pad_color = pad_color
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def coco_eval_with_json(anno_json, pred_json):
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from pycocotools.coco import COCO
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from pycocotools.cocoeval import COCOeval
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anno = COCO(anno_json)
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pred = anno.loadRes(pred_json)
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eval = COCOeval(anno, pred, 'bbox')
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# eval.params.useCats = 0
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# eval.params.maxDets = list((100, 300, 1000))
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# a = np.array(list(range(50, 96, 1)))/100
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# eval.params.iouThrs = a
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eval.evaluate()
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eval.accumulate()
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eval.summarize()
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map, map50 = eval.stats[:2] # update results (mAP@0.5:0.95, mAP@0.5)
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print('map --> ', map)
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print('map50--> ', map50)
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print('map75--> ', eval.stats[2])
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print('map85--> ', eval.stats[-2])
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print('map95--> ', eval.stats[-1])
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class COCO_test_helper():
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def __init__(self, enable_letter_box = False) -> None:
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self.record_list = []
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self.enable_ltter_box = enable_letter_box
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if self.enable_ltter_box is True:
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self.letter_box_info_list = []
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else:
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self.letter_box_info_list = None
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def letter_box(self, im, new_shape, pad_color=(0,0,0), info_need=False):
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# Resize and pad image while meeting stride-multiple constraints
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shape = im.shape[:2] # current shape [height, width]
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if isinstance(new_shape, int):
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new_shape = (new_shape, new_shape)
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# Scale ratio
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r = min(new_shape[0] / shape[0], new_shape[1] / shape[1])
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# Compute padding
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ratio = r # width, height ratios
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new_unpad = int(round(shape[1] * r)), int(round(shape[0] * r))
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dw, dh = new_shape[1] - new_unpad[0], new_shape[0] - new_unpad[1] # wh padding
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dw /= 2 # divide padding into 2 sides
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dh /= 2
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if shape[::-1] != new_unpad: # resize
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im = cv2.resize(im, new_unpad, interpolation=cv2.INTER_LINEAR)
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top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1))
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left, right = int(round(dw - 0.1)), int(round(dw + 0.1))
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im = cv2.copyMakeBorder(im, top, bottom, left, right, cv2.BORDER_CONSTANT, value=pad_color) # add border
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if self.enable_ltter_box is True:
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self.letter_box_info_list.append(Letter_Box_Info(shape, new_shape, ratio, ratio, dw, dh, pad_color))
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if info_need is True:
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return im, ratio, (dw, dh)
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else:
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return im
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def direct_resize(self, im, new_shape, info_need=False):
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shape = im.shape[:2]
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h_ratio = new_shape[0]/ shape[0]
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w_ratio = new_shape[1]/ shape[1]
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if self.enable_ltter_box is True:
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self.letter_box_info_list.append(Letter_Box_Info(shape, new_shape, w_ratio, h_ratio, 0, 0, (0,0,0)))
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im = cv2.resize(im, (new_shape[1], new_shape[0]))
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return im
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def get_real_box(self, box, in_format='xyxy'):
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bbox = copy(box)
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if self.enable_ltter_box == True:
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# unletter_box result
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if in_format=='xyxy':
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bbox[:,0] -= self.letter_box_info_list[-1].dw
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bbox[:,0] /= self.letter_box_info_list[-1].w_ratio
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bbox[:,0] = np.clip(bbox[:,0], 0, self.letter_box_info_list[-1].origin_shape[1])
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bbox[:,1] -= self.letter_box_info_list[-1].dh
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bbox[:,1] /= self.letter_box_info_list[-1].h_ratio
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bbox[:,1] = np.clip(bbox[:,1], 0, self.letter_box_info_list[-1].origin_shape[0])
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bbox[:,2] -= self.letter_box_info_list[-1].dw
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bbox[:,2] /= self.letter_box_info_list[-1].w_ratio
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bbox[:,2] = np.clip(bbox[:,2], 0, self.letter_box_info_list[-1].origin_shape[1])
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bbox[:,3] -= self.letter_box_info_list[-1].dh
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bbox[:,3] /= self.letter_box_info_list[-1].h_ratio
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bbox[:,3] = np.clip(bbox[:,3], 0, self.letter_box_info_list[-1].origin_shape[0])
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return bbox
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def get_real_seg(self, seg):
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#! fix side effect
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dh = int(self.letter_box_info_list[-1].dh)
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dw = int(self.letter_box_info_list[-1].dw)
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origin_shape = self.letter_box_info_list[-1].origin_shape
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new_shape = self.letter_box_info_list[-1].new_shape
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if (dh == 0) and (dw == 0) and origin_shape == new_shape:
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return seg
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elif dh == 0 and dw != 0:
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seg = seg[:, :, dw:-dw] # a[0:-0] = []
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elif dw == 0 and dh != 0 :
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seg = seg[:, dh:-dh, :]
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seg = np.where(seg, 1, 0).astype(np.uint8).transpose(1,2,0)
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seg = cv2.resize(seg, (origin_shape[1], origin_shape[0]), interpolation=cv2.INTER_LINEAR)
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if len(seg.shape) < 3:
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return seg[None,:,:]
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else:
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return seg.transpose(2,0,1)
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def add_single_record(self, image_id, category_id, bbox, score, in_format='xyxy', pred_masks = None):
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if self.enable_ltter_box == True:
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# unletter_box result
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if in_format=='xyxy':
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bbox[0] -= self.letter_box_info_list[-1].dw
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bbox[0] /= self.letter_box_info_list[-1].w_ratio
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bbox[1] -= self.letter_box_info_list[-1].dh
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bbox[1] /= self.letter_box_info_list[-1].h_ratio
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bbox[2] -= self.letter_box_info_list[-1].dw
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bbox[2] /= self.letter_box_info_list[-1].w_ratio
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bbox[3] -= self.letter_box_info_list[-1].dh
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bbox[3] /= self.letter_box_info_list[-1].h_ratio
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# bbox = [value/self.letter_box_info_list[-1].ratio for value in bbox]
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if in_format=='xyxy':
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# change xyxy to xywh
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bbox[2] = bbox[2] - bbox[0]
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bbox[3] = bbox[3] - bbox[1]
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else:
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assert False, "now only support xyxy format, please add code to support others format"
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def single_encode(x):
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from pycocotools.mask import encode
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rle = encode(np.asarray(x[:, :, None], order="F", dtype="uint8"))[0]
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rle["counts"] = rle["counts"].decode("utf-8")
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return rle
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if pred_masks is None:
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self.record_list.append({"image_id": image_id,
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"category_id": category_id,
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"bbox":[round(x, 3) for x in bbox],
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'score': round(score, 5),
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})
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else:
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rles = single_encode(pred_masks)
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self.record_list.append({"image_id": image_id,
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"category_id": category_id,
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"bbox":[round(x, 3) for x in bbox],
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'score': round(score, 5),
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'segmentation': rles,
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})
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def export_to_json(self, path):
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with open(path, 'w') as f:
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json.dump(self.record_list, f)
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