[test] ocr.py example test and add one test figure

Author: GNEHUY

EduNLP/SIF/parser/ocr.py

@@ -4,12 +4,14 @@
 import requests
 from EduNLP.utils import image2base64
 
+
 class FormulaRecognitionError(Exception):
     """Exception raised when formula recognition fails."""
     def __init__(self, message="Formula recognition failed"):
         self.message = message
         super().__init__(self.message)
 
+
 def ocr_formula_figure(image_PIL_or_base64, is_base64=False):
     """
     Recognizes mathematical formulas in an image and returns their LaTeX representation.
@@ -19,26 +21,38 @@ def ocr_formula_figure(image_PIL_or_base64, is_base64=False):
     image_PIL_or_base64 : PngImageFile or str
         The PngImageFile if is_base64 is False, or the base64 encoded string of the image if is_base64 is True.
     is_base64 : bool, optional
-        Indicates whether the image_PIL_or_base64 parameter is an PngImageFile or a base64 encoded string, by default False.
+        Indicates whether the image_PIL_or_base64 parameter is an PngImageFile or a base64 encoded string.
 
     Returns
     -------
     latex : str
-        The LaTeX representation of the mathematical formula recognized in the image. Raises an exception if the image is not recognized as containing a mathematical formula.
+        The LaTeX representation of the mathematical formula recognized in the image.
+        Raises an exception if the image is not recognized as containing a mathematical formula.
 
     Raises
     ------
     FormulaRecognitionError
-        If the HTTP request does not return a 200 status code, if there is an error processing the response, or if the image is not recognized as a mathematical formula.
+        If the HTTP request does not return a 200 status code,
+        if there is an error processing the response,
+        if the image is not recognized as a mathematical formula.
 
     Examples
     --------
+    >>> import os
     >>> from PIL import Image
-    >>> image_PIL = Image.open("path/to/your/image.jpg")
+    >>> from EduNLP.utils import abs_current_dir, path_append
+    >>> img_dir = os.path.abspath(path_append(abs_current_dir(__file__), "..", "..", "..", "asset", "_static"))
+    >>> image_PIL = Image.open(path_append(img_dir, "item_ocr_formula.png", to_str=True))
     >>> print(ocr_formula_figure(image_PIL))
-    Or
-    >>> image_base64 = "base64_encoded_image_string"
+    f(x)=\\left (\\frac {1}{3}\\right )^{x}-\\sqrt {x}}
+    >>> import os
+    >>> from PIL import Image
+    >>> from EduNLP.utils import abs_current_dir, path_append, image2base64
+    >>> img_dir = os.path.abspath(path_append(abs_current_dir(__file__), "..", "..", "..", "asset", "_static"))
+    >>> image_PIL = Image.open(path_append(img_dir, "item_ocr_formula.png", to_str=True))
+    >>> image_base64 = image2base64(image_PIL)
     >>> print(ocr_formula_figure(image_base64, is_base64=True))
+    f(x)=\\left (\\frac {1}{3}\\right )^{x}-\\sqrt {x}}
 
     Notes
     -----
@@ -74,41 +88,59 @@ def ocr_formula_figure(image_PIL_or_base64, is_base64=False):
     else:
         latex = None
         raise FormulaRecognitionError("Image is not recognized as a formula")
-    
+
     return latex
- 
+
+
 def ocr(src, is_base64=False, figure_instances: dict = None):
     """
-    Recognizes mathematical formulas within figures from a given source, which can be either a base64 string or an identifier for a figure within a provided dictionary.
+    Recognizes mathematical formulas within figures from a given source,
+    which can be either a base64 string or an identifier for a figure within a provided dictionary.
 
     Parameters
     ----------
     src : str
-        The source from which the figure is to be recognized. It can be a base64 encoded string of the image if is_base64 is True, or an identifier for the figure if is_base64 is False.
+        The source from which the figure is to be recognized.
+        It can be a base64 encoded string of the image if is_base64 is True,
+        or an identifier for the figure if is_base64 is False.
     is_base64 : bool, optional
         Indicates whether the src parameter is a base64 encoded string or an identifier, by default False.
     figure_instances : dict, optional
-        A dictionary mapping figure identifiers to their corresponding PngImageFile, by default None. This is only required and used if is_base64 is False.
+        A dictionary mapping figure identifiers to their corresponding PngImageFile, by default None.
+        This is only required and used if is_base64 is False.
 
     Returns
     -------
     forumla_figure_latex : str or None
-        The LaTeX representation of the mathematical formula recognized within the figure. Returns None if no formula is recognized or if the figure_instances dictionary does not contain the specified figure identifier when is_base64 is False.
+        The LaTeX representation of the mathematical formula recognized within the figure.
+        Returns None if no formula is recognized or
+        if the figure_instances dictionary does not contain the specified figure identifier when is_base64 is False.
 
     Examples
     --------
-    >>> src_base64 = r"\FormFigureBase64{base64_encoded_image_string}"
-    >>> print(ocr(src_base64, is_base64=True))
-    Or
+    >>> import os
     >>> from PIL import Image
-    >>> image_PIL = Image.open("path/to/your/image.jpg")
-    >>> figure_instances = {"figure1": image_PIL}
-    >>> src_id = r"\FormFigureID{figure1}"
-    >>> print(ocr(src_id, figure_instances=figure_instances))
+    >>> from EduNLP.utils import abs_current_dir, path_append
+    >>> img_dir = os.path.abspath(path_append(abs_current_dir(__file__), "..", "..", "..", "asset", "_static"))
+    >>> image_PIL = Image.open(path_append(img_dir, "item_ocr_formula.png", to_str=True))
+    >>> figure_instances = {"1": image_PIL}
+    >>> src_id = r"$\\FormFigureID{1}$"
+    >>> print(ocr(src_id[1:-1], figure_instances=figure_instances))
+    f(x)=\\left (\\frac {1}{3}\\right )^{x}-\\sqrt {x}}
+    >>> import os
+    >>> from PIL import Image
+    >>> from EduNLP.utils import abs_current_dir, path_append, image2base64
+    >>> img_dir = os.path.abspath(path_append(abs_current_dir(__file__), "..", "..", "..", "asset", "_static"))
+    >>> image_PIL = Image.open(path_append(img_dir, "item_ocr_formula.png", to_str=True))
+    >>> image_base64 = image2base64(image_PIL)
+    >>> src_base64 = r"$\\FormFigureBase64{%s}$" % (image_base64)
+    >>> print(ocr(src_base64[1:-1], is_base64=True, figure_instances=True))
+    f(x)=\\left (\\frac {1}{3}\\right )^{x}-\\sqrt {x}}
 
     Notes
     -----
-    This function relies on `ocr_formula_figure` for the actual OCR (Optical Character Recognition) process. Ensure that `ocr_formula_figure` is correctly implemented and can handle both base64 encoded strings and PngImageFile as input.
+    This function relies on `ocr_formula_figure` for the actual OCR (Optical Character Recognition) process.
+    Ensure that `ocr_formula_figure` is correctly implemented and can handle base64 encoded strings and PngImageFile.
     """
     forumla_figure_latex = None
     if is_base64:
@@ -120,8 +152,5 @@ def ocr(src, is_base64=False, figure_instances: dict = None):
         if figure_instances is not None:
             figure = figure_instances[figure]
             forumla_figure_latex = ocr_formula_figure(figure, is_base64)
-    
-    return forumla_figure_latex
-
-
 
+    return forumla_figure_latex