dataturks格式转sbd格式

柔光的暖阳◎ 2022-10-07 04:52 158阅读 0赞

def getbox(cnt):
        rect = cv2.minAreaRect(cnt) # 得到最小外接矩形的（中心(x,y), (宽,高), 旋转角度）
        box = cv2.boxPoints(rect) # 获取最小外接矩形的4个顶点坐标(ps: cv2.boxPoints(rect) for OpenCV 3.x)
        # box = np.int(box)
        return [int(np.min(box[:,0])),int(np.min(box[:,1])),int(np.max(box[:,0])),int(np.max(box[:,1]))]
    
    imgname = 0
    SbdDict = {
        }
    ImagesList = []
    AnnotationsList = []
    imgids = 0
    annotationids = 0
    imgrootdir = '/home/lhq/segmentation/snake-master/data/sbd/img'
    with open('ice cream.json') as f:
        datas = f.readlines()
        for data in datas:
            data = data.strip()
            Dict = json.loads(data)
    
            content = Dict['content'].split('___')[-1].split('.')[-1]
            content = str(imgname) + '.' + content
            imgname += 1
            Dict['content'] = content
    
            imgdict = {
        }
            imgdict['file_name'] = Dict['content']
            H,W,_ = cv2.imread(os.path.join(imgrootdir,Dict['content'])).shape
            imgdict['height'] = H
            imgdict['width'] = W
            imgdict['id'] = imgids
            ImagesList.append(imgdict)
            annotations = Dict['annotation']
            for annotation in annotations:
                annotationdict = {
        }
                segmentationlist = []
                points = annotation['points']
                for point in points:
                    point[0] = int(point[0] * W)
                    point[1] = int(point[1] * H)
                    segmentationlist.append(point[0])
                    segmentationlist.append(point[1])
                area = cv2.contourArea(np.array(points))
                annotationdict['segmentation'] = [segmentationlist]
                annotationdict['area'] = area
                annotationdict['image_id'] = imgids
                box = getbox(np.array(points))
                annotationdict['bbox'] = box
                annotationdict['iscrowd'] = 0
                annotationdict['id'] = annotationids
                annotationdict['category_id'] = 1
                annotationids += 1
                AnnotationsList.append(annotationdict)
            imgids += 1
    
    with open('/home/lhq/centernettrain/icecream.json') as f:
        datas = f.readlines()
        for data in datas:
            data = data.strip()
            Dict = json.loads(data)
    
            content = Dict['content'].split('___xgbz_')[-1]
            Dict['content'] = content
    
            imgdict = {
        }
            imgdict['file_name'] = Dict['content']
            H,W,_ = cv2.imread(os.path.join(imgrootdir,Dict['content'])).shape
            imgdict['height'] = H
            imgdict['width'] = W
            imgdict['id'] = imgids
            ImagesList.append(imgdict)
            annotations = Dict['annotation']
            for annotation in annotations:
                annotationdict = {
        }
                segmentationlist = []
                points = annotation['points']
                for point in points:
                    point[0] = int(point[0] * W)
                    point[1] = int(point[1] * H)
                    segmentationlist.append(point[0])
                    segmentationlist.append(point[1])
                area = cv2.contourArea(np.array(points))
                annotationdict['segmentation'] = [segmentationlist]
                annotationdict['area'] = area
                annotationdict['image_id'] = imgids
                box = getbox(np.array(points))
                annotationdict['bbox'] = box
                annotationdict['iscrowd'] = 0
                annotationdict['id'] = annotationids
                annotationdict['category_id'] = 1
                annotationids += 1
                AnnotationsList.append(annotationdict)
            imgids += 1
    
    with open('icecream_6_8.json') as f:
        datas = f.readlines()
        for data in datas:
            data = data.strip()
            Dict = json.loads(data)
    
            content = Dict['content'].split('___dataturks_')[-1]
            Dict['content'] = content
    
            imgdict = {
        }
            imgdict['file_name'] = Dict['content']
            H,W,_ = cv2.imread(os.path.join(imgrootdir,Dict['content'])).shape
            imgdict['height'] = H
            imgdict['width'] = W
            imgdict['id'] = imgids
            ImagesList.append(imgdict)
            annotations = Dict['annotation']
            for annotation in annotations:
                annotationdict = {
        }
                segmentationlist = []
                points = annotation['points']
                for point in points:
                    point[0] = int(point[0] * W)
                    point[1] = int(point[1] * H)
                    segmentationlist.append(point[0])
                    segmentationlist.append(point[1])
                area = cv2.contourArea(np.array(points))
                annotationdict['segmentation'] = [segmentationlist]
                annotationdict['area'] = area
                annotationdict['image_id'] = imgids
                box = getbox(np.array(points))
                annotationdict['bbox'] = box
                annotationdict['iscrowd'] = 0
                annotationdict['id'] = annotationids
                annotationdict['category_id'] = 1
                annotationids += 1
                AnnotationsList.append(annotationdict)
            imgids += 1
    
    SbdDict['images'] = ImagesList
    SbdDict['annotations'] = AnnotationsList
    SbdDict['categories'] = [{
        'supercategory': 'none', 'id': 1, 'name': 'icecream'}]
    with open('train.json','w') as fw:
        json.dump(SbdDict,fw)