opt db inference doc
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@ -128,24 +128,32 @@ python3 tools/export_model.py -c configs/cls/cls_mv3.yml -o Global.pretrained_mo
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超轻量中文检测模型推理,可以执行如下命令:
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```
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/"
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# 下载超轻量中文检测模型:
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wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar
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tar xf ch_ppocr_mobile_v2.0_det_infer.tar
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./ch_ppocr_mobile_v2.0_det_infer/"
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```
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可视化文本检测结果默认保存到`./inference_results`文件夹里面,结果文件的名称前缀为'det_res'。结果示例如下:
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![](../imgs_results/det_res_2.jpg)
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![](../imgs_results/det_res_22.jpg)
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通过参数`limit_type`和`det_limit_side_len`来对图片的尺寸进行限制限,`limit_type=max`为限制长边长度<`det_limit_side_len`,`limit_type=min`为限制短边长度>`det_limit_side_len`,
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图片不满足限制条件时(`limit_type=max`时长边长度>`det_limit_side_len`或`limit_type=min`时短边长度<`det_limit_side_len`),将对图片进行等比例缩放。
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该参数默认设置为`limit_type='max',det_max_side_len=960`。 如果输入图片的分辨率比较大,而且想使用更大的分辨率预测,可以执行如下命令:
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通过参数`limit_type`和`det_limit_side_len`来对图片的尺寸进行限制,
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`litmit_type`可选参数为[`max`, `min`],
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`det_limit_size_len` 为正整数,一般设置为32 的倍数,比如960。
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参数默认设置为`limit_type='max', det_limit_side_len=960`。表示网络输入图像的最长边不能超过960,
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如果超过这个值,会对图像做等宽比的resize操作,确保最长边为`det_limit_side_len`。
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设置为`limit_type='min', det_limit_side_len=960` 则表示限制图像的最短边为960。
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如果输入图片的分辨率比较大,而且想使用更大的分辨率预测,可以设置det_limit_side_len 为想要的值,比如1216:
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```
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1200
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1216
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```
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如果想使用CPU进行预测,执行命令如下
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```
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False
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```
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<a name="DB文本检测模型推理"></a>
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@ -165,7 +173,7 @@ python3 tools/infer/predict_det.py --image_dir="./doc/imgs_en/img_10.jpg" --det_
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可视化文本检测结果默认保存到`./inference_results`文件夹里面,结果文件的名称前缀为'det_res'。结果示例如下:
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![](../imgs_results/det_res_img_10_db.jpg)
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![](../imgs_results/det_res_22.jpg)
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**注意**:由于ICDAR2015数据集只有1000张训练图像,且主要针对英文场景,所以上述模型对中文文本图像检测效果会比较差。
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@ -134,24 +134,33 @@ Because EAST and DB algorithms are very different, when inference, it is necessa
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For lightweight Chinese detection model inference, you can execute the following commands:
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```
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/"
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# download DB text detection inference model
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wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar
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tar xf ch_ppocr_mobile_v2.0_det_infer.tar
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# predict
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./inference/det_db/"
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```
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The visual text detection results are saved to the ./inference_results folder by default, and the name of the result file is prefixed with'det_res'. Examples of results are as follows:
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![](../imgs_results/det_res_2.jpg)
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![](../imgs_results/det_res_22.jpg)
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The size of the image is limited by the parameters `limit_type` and `det_limit_side_len`, `limit_type=max` is to limit the length of the long side <`det_limit_side_len`, and `limit_type=min` is to limit the length of the short side>`det_limit_side_len`,
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When the picture does not meet the restriction conditions (for `limit_type=max`and long side >`det_limit_side_len` or for `min` and short side <`det_limit_side_len`), the image will be scaled proportionally.
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This parameter is set to `limit_type='max', det_max_side_len=960` by default. If the resolution of the input picture is relatively large, and you want to use a larger resolution prediction, you can execute the following command:
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You can use the parameters `limit_type` and `det_limit_side_len` to limit the size of the input image,
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The optional parameters of `litmit_type` are [`max`, `min`], and
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`det_limit_size_len` is a positive integer, generally set to a multiple of 32, such as 960.
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The default setting of the parameters is `limit_type='max', det_limit_side_len=960`. Indicates that the longest side of the network input image cannot exceed 960,
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If this value is exceeded, the image will be resized with the same width ratio to ensure that the longest side is `det_limit_side_len`.
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Set as `limit_type='min', det_limit_side_len=960`, it means that the shortest side of the image is limited to 960.
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If the resolution of the input picture is relatively large and you want to use a larger resolution prediction, you can set det_limit_side_len to the desired value, such as 1216:
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```
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1200
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2s.jpg" --det_model_dir="./inference/det_db/" --det_limit_type=max --det_limit_side_len=1216
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```
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If you want to use the CPU for prediction, execute the command as follows
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```
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False
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python3 tools/infer/predict_det.py --image_dir="./doc/imgs/2s.jpg" --det_model_dir="./inference/det_db/" --use_gpu=False
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```
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<a name="DB_DETECTION"></a>
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