Spaces:
Sleeping
Sleeping
Update modules/preprocessing.py
Browse files- modules/preprocessing.py +21 -19
modules/preprocessing.py
CHANGED
@@ -97,25 +97,27 @@ class PDFProcessor:
|
|
97 |
self.ocr_model = ocr_predictor(pretrained=True)
|
98 |
self.max_pages = max_pages
|
99 |
|
100 |
-
def pdf_to_text(
|
101 |
-
|
102 |
-
|
103 |
-
|
104 |
-
|
105 |
-
|
106 |
-
|
107 |
-
#
|
108 |
-
|
109 |
-
|
110 |
-
|
111 |
-
|
112 |
-
|
113 |
-
|
114 |
-
|
115 |
-
|
116 |
-
|
117 |
-
|
118 |
-
|
|
|
|
|
119 |
|
120 |
|
121 |
|
|
|
97 |
self.ocr_model = ocr_predictor(pretrained=True)
|
98 |
self.max_pages = max_pages
|
99 |
|
100 |
+
def pdf_to_text(pdf_path):
|
101 |
+
# 1) Cargar el PDF
|
102 |
+
doc = DocumentFile.from_pdf(pdf_path)
|
103 |
+
|
104 |
+
# 2) Crear un predictor (modelo OCR); docTR brinda modelos preentrenados
|
105 |
+
predictor = ocr_predictor(pretrained=True)
|
106 |
+
|
107 |
+
# 3) Aplicar el predictor al documento para obtener el layout
|
108 |
+
ocr_result = predictor(doc)
|
109 |
+
|
110 |
+
# Ahora sí, las páginas tienen .blocks, .lines, etc.
|
111 |
+
pages = ocr_result.pages
|
112 |
+
|
113 |
+
# 4) Extraer el texto de cada bloque
|
114 |
+
text_pages = []
|
115 |
+
for page in pages:
|
116 |
+
for block in page.blocks:
|
117 |
+
text_pages.append(block.text)
|
118 |
+
|
119 |
+
# 5) Unir o procesar a conveniencia
|
120 |
+
return "\n".join(text_pages)
|
121 |
|
122 |
|
123 |
|