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release-2.
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@@ -43,6 +43,10 @@
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</div>
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# Changelog
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- 2025/07/28 version 2.1.8 Released
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- `sglang` 0.4.9.post5 version adaptation
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- 2025/07/27 version 2.1.7 Released
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- `transformers` 4.54.0 version adaptation
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- 2025/07/26 2.1.6 Released
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- Fixed table parsing issues in handwritten documents when using `vlm` backend
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- Fixed visualization box position drift issue when document is rotated #3175
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@@ -43,16 +43,20 @@
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</div>
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# 更新记录
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- 2025/07/26 2.1.6发布
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- 2025/07/28 2.1.8 发布
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- `sglang` 0.4.9.post5 版本适配
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- 2025/07/27 2.1.7 发布
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- `transformers` 4.54.0 版本适配
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- 2025/07/26 2.1.6 发布
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- 修复`vlm`后端解析部分手写文档时的表格异常问题
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- 修复文档旋转时可视化框位置漂移问题 #3175
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- 2025/07/24 2.1.5发布
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- 2025/07/24 2.1.5 发布
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- `sglang` 0.4.9 版本适配,同步升级dockerfile基础镜像为sglang 0.4.9.post3
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- 2025/07/23 2.1.4发布
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- 2025/07/23 2.1.4 发布
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- bug修复
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- 修复`pipeline`后端中`MFR`步骤在某些情况下显存消耗过大的问题 #2771
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- 修复某些情况下`image`/`table`与`caption`/`footnote`匹配不准确的问题 #3129
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- 2025/07/16 2.1.1发布
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- 2025/07/16 2.1.1 发布
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- bug修复
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- 修复`pipeline`在某些情况可能发生的文本块内容丢失问题 #3005
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- 修复`sglang-client`需要安装`torch`等不必要的包的问题 #2968
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@@ -60,7 +64,7 @@
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- 易用性更新
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- 更新`compose.yaml`,便于用户直接启动`sglang-server`、`mineru-api`、`mineru-gradio`服务
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- 启用全新的[在线文档站点](https://opendatalab.github.io/MinerU/zh/),简化readme,提供更好的文档体验
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- 2025/07/05 2.1.0发布
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- 2025/07/05 2.1.0 发布
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- 这是 MinerU 2 的第一个大版本更新,包含了大量新功能和改进,包含众多性能优化、体验优化和bug修复,具体更新内容如下:
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- 性能优化:
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- 大幅提升某些特定分辨率(长边2000像素左右)文档的预处理速度
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@@ -1,7 +1,7 @@
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# Use the official sglang image
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FROM lmsysorg/sglang:v0.4.9.post3-cu126
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FROM lmsysorg/sglang:v0.4.9.post5-cu126
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# For blackwell GPU, use the following line instead:
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# FROM lmsysorg/sglang:v0.4.9.post3-cu128-b200
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# FROM lmsysorg/sglang:v0.4.9.post5-cu128-b200
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# Install libgl for opencv support & Noto fonts for Chinese characters
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RUN apt-get update && \
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@@ -1,7 +1,7 @@
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# Use the official sglang image
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FROM lmsysorg/sglang:v0.4.9.post3-cu126
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FROM lmsysorg/sglang:v0.4.9.post5-cu126
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# For blackwell GPU, use the following line instead:
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# FROM lmsysorg/sglang:v0.4.9.post3-cu128-b200
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# FROM lmsysorg/sglang:v0.4.9.post5-cu128-b200
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# Install libgl for opencv support & Noto fonts for Chinese characters
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RUN apt-get update && \
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@@ -10,8 +10,8 @@ docker build -t mineru-sglang:latest -f Dockerfile .
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```
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> [!TIP]
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> The [Dockerfile](https://github.com/opendatalab/MinerU/blob/master/docker/global/Dockerfile) uses `lmsysorg/sglang:v0.4.9.post3-cu126` as the base image by default, supporting Turing/Ampere/Ada Lovelace/Hopper platforms.
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> If you are using the newer `Blackwell` platform, please modify the base image to `lmsysorg/sglang:v0.4.9.post3-cu128-b200` before executing the build operation.
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> The [Dockerfile](https://github.com/opendatalab/MinerU/blob/master/docker/global/Dockerfile) uses `lmsysorg/sglang:v0.4.9.post5-cu126` as the base image by default, supporting Turing/Ampere/Ada Lovelace/Hopper platforms.
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> If you are using the newer `Blackwell` platform, please modify the base image to `lmsysorg/sglang:v0.4.9.post5-cu128-b200` before executing the build operation.
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## Docker Description
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@@ -10,8 +10,8 @@ docker build -t mineru-sglang:latest -f Dockerfile .
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```
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> [!TIP]
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> [Dockerfile](https://github.com/opendatalab/MinerU/blob/master/docker/china/Dockerfile)默认使用`lmsysorg/sglang:v0.4.9.post3-cu126`作为基础镜像,支持Turing/Ampere/Ada Lovelace/Hopper平台,
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> 如您使用较新的`Blackwell`平台,请将基础镜像修改为`lmsysorg/sglang:v0.4.9.post3-cu128-b200` 再执行build操作。
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> [Dockerfile](https://github.com/opendatalab/MinerU/blob/master/docker/china/Dockerfile)默认使用`lmsysorg/sglang:v0.4.9.post5-cu126`作为基础镜像,支持Turing/Ampere/Ada Lovelace/Hopper平台,
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> 如您使用较新的`Blackwell`平台,请将基础镜像修改为`lmsysorg/sglang:v0.4.9.post5-cu128-b200` 再执行build操作。
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## Docker说明
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@@ -1416,7 +1416,11 @@ class UnimerMBartDecoder(UnimerMBartPreTrainedModel):
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raise ValueError("You have to specify either decoder_input_ids or decoder_inputs_embeds")
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# past_key_values_length
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past_key_values_length = past_key_values[0][0].shape[2] if past_key_values is not None else 0
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# past_key_values_length = past_key_values[0][0].shape[2] if past_key_values is not None else 0
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past_key_values_length = 0
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if past_key_values is not None:
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if isinstance(past_key_values, (list, tuple)) and past_key_values:
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past_key_values_length = past_key_values[0][0].shape[2]
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if inputs_embeds is None:
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inputs_embeds = self.embed_tokens(input_ids)
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@@ -1501,7 +1505,12 @@ class UnimerMBartDecoder(UnimerMBartPreTrainedModel):
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if dropout_probability < self.layerdrop:
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continue
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past_key_value = past_key_values[idx] if past_key_values is not None else None
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# past_key_value = past_key_values[idx] if past_key_values is not None else None
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past_key_value = past_key_values[idx] if (
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past_key_values is not None and
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isinstance(past_key_values, (list, tuple)) and
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idx < len(past_key_values)
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) else None
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if self.gradient_checkpointing and self.training:
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layer_outputs = self._gradient_checkpointing_func(
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@@ -56,8 +56,8 @@ def process_anyres_image(image, processor, grid_pinpoints):
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class Mineru2ImageProcessor(BaseProcessor):
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def __init__(self, hf_config, server_args, _processor):
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super().__init__(hf_config, server_args, _processor)
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def __init__(self, hf_config, server_args, _processor, *args, **kwargs):
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super().__init__(hf_config, server_args, _processor, *args, **kwargs)
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@staticmethod
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def _process_single_image_task(
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@@ -1 +1 @@
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__version__ = "2.1.5"
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__version__ = "2.1.7"
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