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@brooklyn1900 作者您好,我在跑train_synthText.py的时候,发现生成高斯热力图的函数执行太慢,可能是导致GPU利用率过低的原因,请问有没有高效的算法?
#获取图片的高斯热力图 def get_region_scores(self, heat_map_size, char_boxes_list): # 高斯热力图 gaussian_generator = GaussianGenerator() region_scores = gaussian_generator.gen(heat_map_size, char_boxes_list) return region_scores
The text was updated successfully, but these errors were encountered:
@brooklyn1900 作者您好,我在跑train_synthText.py的时候,发现生成高斯热力图的函数执行太慢,可能是导致GPU利用率过低的原因,请问有没有高效的算法? #获取图片的高斯热力图 def get_region_scores(self, heat_map_size, char_boxes_list): # 高斯热力图 gaussian_generator = GaussianGenerator() region_scores = gaussian_generator.gen(heat_map_size, char_boxes_list) return region_scores
你好,请问您解决了吗
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@jelly-Ding 我先把所有数据事先处理完,单独保存为npy文件,训练的时候直接np.load。建议在固态硬盘上操作,机械硬盘读取一样会慢。
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@brooklyn1900 作者您好,我在跑train_synthText.py的时候,发现生成高斯热力图的函数执行太慢,可能是导致GPU利用率过低的原因,请问有没有高效的算法?
#获取图片的高斯热力图 def get_region_scores(self, heat_map_size, char_boxes_list): # 高斯热力图 gaussian_generator = GaussianGenerator() region_scores = gaussian_generator.gen(heat_map_size, char_boxes_list) return region_scores
The text was updated successfully, but these errors were encountered: