predict_table.py: error: argument --det_model_dir: expected one argument

This error message indicates that the program "predict_table.py" is expecting an argument for the parameter "--det_model_dir", but none was provided.

To fix this error, you need to provide the path to the directory where the detection model is stored as an argument for the "--det_model_dir" parameter. For example, if the detection model is stored in a directory called "models/table_detector", you would run the program with the following command:

python predict_table.py --det_model_dir models/table_detector

Make sure to replace "models/table_detector" with the actual path to your detection model directory.

相关问题

AttributeError Traceback (most recent call last) Cell In[21], line 62 60 softmax_probs = softmax_model.predict_proba(X_test_scaled) 61 mlp_probs = mlp_model.predict_proba(X_test_scaled) ---> 62 svm_probs = svm_model.predict_proba(X_test_scaled)[:, 1] 64 softmax_fpr, softmax_tpr, _ = roc_curve(y_test, softmax_probs[:, 1], pos_label=2) 65 mlp_fpr, mlp_tpr, _ = roc_curve(y_test, mlp_probs[:, 1], pos_label=2) File D:\ANACONDA\lib\site-packages\sklearn\utils\_available_if.py:32, in _AvailableIfDescriptor.__get__(self, obj, owner) 26 attr_err = AttributeError( 27 f"This {repr(owner.__name__)} has no attribute {repr(self.attribute_name)}" 28 ) 29 if obj is not None: 30 # delegate only on instances, not the classes. 31 # this is to allow access to the docstrings. ---> 32 if not self.check(obj): 33 raise attr_err 34 out = MethodType(self.fn, obj) File D:\ANACONDA\lib\site-packages\sklearn\svm\_base.py:829, in BaseSVC._check_proba(self) 827 def _check_proba(self): 828 if not self.probability: --> 829 raise AttributeError( 830 "predict_proba is not available when probability=False" 831 ) 832 if self._impl not in ("c_svc", "nu_svc"): 833 raise AttributeError("predict_proba only implemented for SVC and NuSVC") AttributeError: predict_proba is not available when probability=False

这个错误是由于支持向量机模型（SVC）的probability参数设置为False时，不支持使用predict_proba方法来获取样本属于各个类别的概率导致的。

解决这个问题有两种方法：

1. 将SVC模型的probability参数设置为True。修改代码如下：

svm_model = SVC(kernel='rbf', C=1.0, probability=True)

使用上述代码替换原代码中的`svm_model = SVC(kernel='rbf', C=1.0)`，然后再次运行程序，即可解决该错误。

2. 使用decision_function方法来获取样本距离分类超平面的距离，并手动将其转换为概率值。修改代码如下：

svm_distances = svm_model.decision_function(X_test_scaled)
svm_probs = (svm_distances - svm_distances.min()) / (svm_distances.max() - svm_distances.min())

使用上述代码替换原代码中的`svm_probs = svm_model.predict_proba(X_test_scaled)[:, 1]`，然后再次运行程序，即可解决该错误。

希望这个解决方案能帮助到你！如果还有其他问题，请随时提问。

(single) python tools/infer/predict_cls.py --image_dir="./train_data/rec/val/2d5e74b3b32f8f2f6c3ab24abe19e02e_crop_2.jpg" --cls_model_dir="/output/rec_chinese_common_v2.0/latest" Traceback (most recent call last): File "tools/infer/predict_cls.py", line 156, in <module> main(utility.parse_args()) File "tools/infer/predict_cls.py", line 132, in main text_classifier = TextClassifier(args) File "tools/infer/predict_cls.py", line 54, in __init__ utility.create_predictor(args, 'cls', logger) File "E:\Demo\PaddleOCR-2.6.0\tools\infer\utility.py", line 194, in create_predictor model_dir)) ValueError: not find model.pdmodel or inference.pdmodel in /output/rec_chinese_common_v2.0/latest

这个错误信息表明在你指定的目录`/output/rec_chinese_common_v2.0/latest`中找不到模型文件`model.pdmodel`或者`inference.pdmodel`。这可能是因为这两个文件不存在于指定的目录中，或者指定的目录路径不正确。你可以检查一下文件是否存在，或者检查你指定的路径是否正确。