mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-05-02 20:03:19 +02:00
82 lines
1.8 KiB
Python
Executable file
82 lines
1.8 KiB
Python
Executable file
|
|
"""
|
|
Simple decoder, accepts PDF documents on input, outputs pages from the
|
|
PDF document as text as separate output objects.
|
|
"""
|
|
|
|
import tempfile
|
|
import base64
|
|
import pytesseract
|
|
from pdf2image import convert_from_bytes
|
|
|
|
from ... schema import Document, TextDocument, Metadata
|
|
from ... base import FlowProcessor, ConsumerSpec, ProducerSpec
|
|
|
|
default_ident = "pdf-decoder"
|
|
|
|
class Processor(FlowProcessor):
|
|
|
|
def __init__(self, **params):
|
|
|
|
id = params.get("id", default_ident)
|
|
|
|
super(Processor, self).__init__(
|
|
**params | {
|
|
"id": id,
|
|
}
|
|
)
|
|
|
|
self.register_specification(
|
|
ConsumerSpec(
|
|
name = "input",
|
|
schema = Document,
|
|
handler = self.on_message,
|
|
)
|
|
)
|
|
|
|
self.register_specification(
|
|
ProducerSpec(
|
|
name = "output",
|
|
schema = TextDocument,
|
|
)
|
|
)
|
|
|
|
print("PDF OCR inited")
|
|
|
|
async def on_message(self, msg, consumer, flow):
|
|
|
|
print("PDF message received", flush=True)
|
|
|
|
v = msg.value()
|
|
|
|
print(f"Decoding {v.metadata.id}...", flush=True)
|
|
|
|
blob = base64.b64decode(v.data)
|
|
|
|
pages = convert_from_bytes(blob)
|
|
|
|
for ix, page in enumerate(pages):
|
|
|
|
try:
|
|
text = pytesseract.image_to_string(page, lang='eng')
|
|
except Exception as e:
|
|
print(f"Page did not OCR: {e}")
|
|
continue
|
|
|
|
r = TextDocument(
|
|
metadata=v.metadata,
|
|
text=text.encode("utf-8"),
|
|
)
|
|
|
|
await flow("output").send(r)
|
|
|
|
print("Done.", flush=True)
|
|
|
|
@staticmethod
|
|
def add_args(parser):
|
|
FlowProcessor.add_args(parser)
|
|
|
|
def run():
|
|
|
|
Processor.launch(default_ident, __doc__)
|
|
|