Synced repo using 'sync_with_huggingface' Github Action

gradio_app.py

@@ -0,0 +1,143 @@
+import os
+import sys
+
+from torch import Value
+
+if "APP_PATH" in os.environ:
+    sys.path.append(os.environ["APP_PATH"])
+
+import gradio as gr
+
+from tabled.assignment import assign_rows_columns
+from tabled.fileinput import load_pdfs_images
+from tabled.formats.markdown import markdown_format
+from tabled.inference.detection import detect_tables
+from tabled.inference.recognition import get_cells, recognize_tables
+
+os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
+os.environ["IN_STREAMLIT"] = "true"
+import pypdfium2
+
+import io
+import tempfile
+from PIL import Image
+
+from tabled.inference.models import load_detection_models, load_recognition_models, load_layout_models
+
+def load_models():
+    return load_detection_models(), load_recognition_models(), load_layout_models()
+
+def run_table_rec(image, highres_image, text_line, models, skip_detection=False, detect_boxes=False):
+    if not skip_detection:
+        table_imgs, table_bboxes, _ = detect_tables([image], [highres_image], models[2])
+    else:
+        table_imgs = [highres_image]
+        table_bboxes = [[0, 0, highres_image.size[0], highres_image.size[1]]]
+
+    table_text_lines = [text_line] * len(table_imgs)
+    highres_image_sizes = [highres_image.size] * len(table_imgs)
+    cells, needs_ocr = get_cells(table_imgs, table_bboxes, highres_image_sizes, table_text_lines, models[0], detect_boxes=detect_boxes)
+
+    table_rec = recognize_tables(table_imgs, cells, needs_ocr, models[1])
+    cells = [assign_rows_columns(tr, im_size) for tr, im_size in zip(table_rec, highres_image_sizes)]
+
+    out_data = []
+    for idx, (cell, pred, table_img) in enumerate(zip(cells, table_rec, table_imgs)):
+        md = markdown_format(cell)
+        out_data.append((md, table_img))
+    return out_data
+
+def open_pdf(pdf_file):
+    return pypdfium2.PdfDocument(pdf_file)
+
+def count_pdf(pdf_file):
+    doc = open_pdf(pdf_file)
+    return len(doc)
+
+def get_page_image(pdf_file, page_num, dpi=96):
+    doc = open_pdf(pdf_file)
+    renderer = doc.render(
+        pypdfium2.PdfBitmap.to_pil,
+        page_indices=[page_num - 1],
+        scale=dpi / 72,
+    )
+    png = list(renderer)[0]
+    png_image = png.convert("RGB")
+    return png_image
+
+def get_uploaded_image(in_file):
+    return Image.open(in_file).convert("RGB")
+
+
+models = load_models()
+
+with gr.Blocks(title="Tabled") as demo:
+    gr.Markdown("""
+    # Tabled Demo
+
+    This app will let you try tabled, a table detection and recognition model.  It will detect and recognize the tables.
+
+    Find the project [here](https://github.com/VikParuchuri/tabled).
+    """)
+
+    with gr.Row():
+        with gr.Column():
+            in_file = gr.File(label="PDF file or image:", file_types=[".pdf", ".png", ".jpg", ".jpeg", ".gif", ".webp"])
+            in_num = gr.Slider(label="Page number", minimum=1, maximum=100, value=1, step=1)
+            in_img = gr.Image(label="Page of Image", type="pil", sources=None)
+
+            skip_detection_ckb = gr.Checkbox(label="Skip table detection", info="Use this if tables are already cropped (the whole PDF page or image is a table)")
+            detect_boxes_ckb = gr.Checkbox(label="Detect cell boxes", info="Detect table cell boxes vs extract from PDF.  Will also run OCR.")
+
+            tabled_btn = gr.Button("Run Tabled")
+        with gr.Column():
+            result_img = gr.Gallery(label="Result images", show_label=False, columns=[1], rows=[10], object_fit="contain", height="auto")
+            result_md = gr.Markdown(label="Result markdown")
+
+        def show_image(file, num=1):
+            if file.endswith('.pdf'):
+                count = count_pdf(file)
+                img = get_page_image(file, num)
+                return [
+                    gr.update(visible=True, maximum=count),
+                    gr.update(value=img)]
+            else:
+                img = get_uploaded_image(file)
+                return [
+                    gr.update(visible=False),
+                    gr.update(value=img)]
+
+        in_file.upload(
+            fn=show_image,
+            inputs=[in_file],
+            outputs=[in_num, in_img],
+        )
+        in_num.change(
+            fn=show_image,
+            inputs=[in_file, in_num],
+            outputs=[in_num, in_img],
+        )
+
+        # Run OCR
+        def text_rec_img(in_file, page_number, skip_detection, detect_boxes):
+            images, highres_images, names, text_lines = load_pdfs_images(in_file, max_pages=1, start_page=page_number - 1)
+
+            out_data = run_table_rec(images[0], highres_images[0], text_lines[0], models, skip_detection=skip_detection, detect_boxes=detect_boxes)
+
+            if len(out_data) == 0:
+                gr.Warning(f"No tables found on page {page_number}", duration=5)
+
+            table_md = ""
+            table_imgs = []
+            for idx, (md, table_img) in enumerate(out_data):
+                table_md += f"\n## Table {idx}\n"
+                table_md += md
+                table_imgs.append(table_img)
+            return gr.update(rows=[len(table_imgs)], value=table_imgs), table_md
+        tabled_btn.click(
+            fn=text_rec_img,
+            inputs=[in_file, in_num, skip_detection_ckb, detect_boxes_ckb],
+            outputs=[result_img, result_md]
+        )
+
+demo.launch()

requirements.txt

@@ -0,0 +1,4 @@
+torch==2.5.1
+tabled-pdf==0.1.7
+gradio==5.8.0
+huggingface-hub==0.26.3