tf_otsl/
tf_otsl.rs

1//! Verify TableFormer inference: run it on every table region of a PDF and print
2//! the predicted OTSL structure. Usage: `... --example tf_otsl -- file.pdf`
3
4use fleischwolf_pdf::layout::LayoutModel;
5use fleischwolf_pdf::tableformer::TableFormer;
6use fleischwolf_pdf::PdfDocument;
7use image::imageops;
8
9fn name(t: i64) -> &'static str {
10    match t {
11        4 => "ecel",
12        5 => "fcel",
13        6 => "lcel",
14        7 => "ucel",
15        8 => "xcel",
16        9 => "nl",
17        10 => "ched",
18        11 => "rhed",
19        12 => "srow",
20        _ => "?",
21    }
22}
23
24fn main() {
25    let path = std::env::args().nth(1).expect("usage: tf_otsl <pdf>");
26    let bytes = std::fs::read(&path).expect("read");
27    let doc = PdfDocument::open(&bytes, None).expect("open");
28    let mut layout = LayoutModel::load().expect("layout");
29    let mut tf = TableFormer::load().expect("tableformer models missing");
30    for (pi, page) in doc.pages.iter().enumerate() {
31        let regions = layout
32            .predict(&page.image, page.width, page.height)
33            .expect("layout");
34        // docling resizes the whole page to 1024px height (cv2.INTER_AREA), then
35        // crops the table bbox out of *that*. Replicate exactly.
36        let sf = 1024.0 / page.image.height() as f32;
37        let pw1024 = (page.image.width() as f32 * sf) as u32; // docling: int(w*r)
38        let page1024 = fleischwolf_pdf::resample::inter_area(&page.image, pw1024, 1024);
39        for r in regions.iter().filter(|r| r.label == "table") {
40            // bbox (points) → 1024px-page coords: scale*sf = 1024/page_h_pt;
41            // docling rounds the crop edges.
42            let k = 1024.0 / page.height;
43            let x = (r.l * k).round().max(0.0) as u32;
44            let y = (r.t * k).round().max(0.0) as u32;
45            let x2 = (r.r * k).round() as u32;
46            let y2 = (r.b * k).round() as u32;
47            let (w, h) = (x2 - x, y2 - y);
48            let crop = imageops::crop_imm(&page1024, x, y, w, h).to_image();
49            let cells = tf.predict_table_structure(&crop).expect("predict");
50            println!(
51                "page {} table {}x{}px -> {} cells",
52                pi + 1,
53                w,
54                h,
55                cells.len()
56            );
57            for c in &cells {
58                println!(
59                    "  r{} c{} {}x{} {} | cxcywh {:.4} {:.4} {:.4} {:.4}",
60                    c.row,
61                    c.col,
62                    c.colspan,
63                    c.rowspan,
64                    name(c.tag),
65                    c.cx,
66                    c.cy,
67                    c.w,
68                    c.h
69                );
70            }
71        }
72    }
73}
tf_otsl/tf_otsl.rs

tf_otsl/
tf_otsl.rs
