CLIPSeg
联合项目
https://github.com/loki-keroro/SAMbase_segmentation?tab=readme-ov-file
模型会根据不同的提示文本，生成不同的掩码，可修改main.py中的category_cfg变量，自定义提示文本。
- landcover_prompts 为地物分类的提示，在全景图中场景下一般用于分割区域连续或新增的类别
- cityobject_prompts 作为实例分割的提示，在全景图中场景下一般用于图像内区域不连续的对象类别
- landcover_prompts_cn和cityobject_prompts_cn为每个类别的中文含义
category_cfg = {"landcover_prompts": ['building', 'low vegetation', 'tree', 'river', 'shed', 'road', 'lake', 'bare soil'],"landcover_prompts_cn": ['建筑', '低矮植被', '树木', '河流', '棚屋', '道路', '湖泊', '裸土'],"cityobject_prompts": ['car', 'truck', 'bus', 'train', 'ship', 'boat'],"cityobject_prompts_cn": ['轿车', '卡车', '巴士', '列车', '船(舰)', '船(舶)']
}
from inference import PSAM# 模型配置文件和权重文件
model_cfg = {"DINO_WEIGHT_PATH": "weights/GSA_weights/groundingdino_swinb_cogcoor.pth","DINO_CFG_PATH": "groundingdino/config/GroundingDINO_SwinB.py","SAM_WEIGHT_PATH": "weights/GSA_weights/sam_vit_h_4b8939.pth","CLIP_WEIGHT_DIR": "weights/CLIP_weights/"
}# prompts提示，可自定义类别列表
# 模型会根据不同的prompts提示，生成不同的掩码
# category_cfg = {
# "landcover_prompts": ['building', 'low vegetation', 'tree', 'water', 'shed', 'road', 'lake', 'bare soil',],
# "landcover_prompts_cn": ['建筑', '低矮植被', '树木', '水体', '棚屋', '道路', '湖泊', '裸土'],
# "cityobject_prompts": ['car', 'truck', 'bus', 'train', 'ship', 'boat'],
# "cityobject_prompts_cn": ['轿车', '卡车', '巴士', '列车', '船(舰)', '船(舶)']
# }
category_cfg = {"landcover_prompts": [ 'building', 'water', 'tree', 'road','shed', 'cropland','grassland', 'Agricultural Fields','bare soil'],"landcover_prompts_cn": ['建筑', '水体', '树木', '道路', '棚屋', '农田', '草地', '农用地','裸土'],"cityobject_prompts": ['car', 'truck','train'],"cityobject_prompts_cn": ['轿车', '货车','火车']
}gpus = ["1"]# matplotlib使用中文绘制
cn_style = False # 是否使用中文
font_style_path = '/usr/share/fonts/wqy-microhei/wqy-microhei.ttc' # 中文字体路径，可通过fc-list命令查看系统中所安装的字体if __name__ == "__main__":psam = PSAM(model_cfg, category_cfg, gpus)# img_path = "/home/piesat/data/无人机全景图/panorama01-04/match_imgs/CD_dataset/01->03/A_B/A/100_right_0_1_hw(2701,672).png"# img_path = "/home/piesat/media/ljh/pycharm_project__ljh/panorama_sam/photos/c1.png"file_path = '/home/piesat/data/无人机全景图/panorama01-04/match_imgs/CD_dataset/cwptys_tmp/A'save_path = '/home/piesat/media/ljh/pycharm_project__ljh/panorama_sam/photos/croplands/'import osfiles = []for root, dirs, filenames in os.walk(file_path):for filename in filenames:in_img_path = os.path.join(root, filename)out_img_path = os.path.join(save_path, filename)psam.load_image(in_img_path)panoptic_inds = psam.generate_panoptic_mask()psam.plt_draw_image(cn_style, font_style_path, out_img_path)print(panoptic_inds.shape) # panoptic_inds：单通道掩码图像