Inference individual Image for table detection

[matchalambada]

Hi authors,
I would like to visualize the result table detection for an specific Image. Which output in the code should I take out and modify in order to have coordianates of predicted bouding box to visualize it on the infered image?

[mzhadigerov]

Is there any update on that?

[Architectshwet]

How can we extract data in rows/column format from the table image from the trained model?

[bsmock]

In the current version of the code, you can find the function that takes the model output and processes it into a table representation here:

table-transformer/src/grits.py

Line 727 in 3e1dd0c

pred_table_structures, pred_cells, pred_confidence_score = objects_to_cells(pred_bboxes, pred_labels, pred_scores,

[Jiangwentai]

@bsmock

hello ,I want to know if I used the Functiuon objects_to_cells ,How can I get the page_tokens if I will use a new Image input

[bsmock]

How can I get the page_tokens if I will use a new Image input

Right now the code is written to be used with the PubTables-1M dataset or any dataset in the same format. For each table image in PubTables-1M, there is also a JSON file with a list of words in the image, which is read in as page_tokens. So the input image and the list of words (page_tokens) are what you need for inference.

You can have a look at the dataset to see examples of the format for page_tokens. Basically page_tokens needs to be a list of dicts, where each dict corresponds to a word or token and looks like this:
{"text": "Table", "bbox": [xmin, ymin, xmax, ymax], "flags": 0, "block_num": 0, "line_num": 0, "span_num": 0}

At a minimum you'll need to fill in the "text", "bbox", and "span_num" fields, where "span_num" is an integer that puts the words in some order. When the code returns the text for each cell as a string, the words in the text string will be sorted by "block_num", then "line_num", then "span_num". So you can leave "flags", "block_num", and "line_num" as 0 as long as you put a unique integer for each word in "span_num".

[jshtok]

@bsmock , Can you please add at least one example image with all the required data structures to make a working inference example? It would help to understand the format without downloading 110Gb of data.
Thank you!

[suonbo]

@bsmock , Can you please add at least one example image with all the required data structures to make a working inference example? It would help to understand the format without downloading 110Gb of data. Thank you!

You can find some samples from here:
https://drive.google.com/drive/folders/0B5h08T2mGP3ffnZLbTZ0WVNRT3Zjdjl2eC11aW0tOFVCaU5Mb2c2Q0dmc21lNWo1Y3BuT3c?resourcekey=0-bphHgPyZKg0yT5V8F7BWjw&usp=sharing

[jshtok]

@bsmock , Can you please add at least one example image with all the required data structures to make a working inference example? It would help to understand the format without downloading 110Gb of data. Thank you!

You can find some samples from here: https://drive.google.com/drive/folders/0B5h08T2mGP3ffnZLbTZ0WVNRT3Zjdjl2eC11aW0tOFVCaU5Mb2c2Q0dmc21lNWo1Y3BuT3c?resourcekey=0-bphHgPyZKg0yT5V8F7BWjw&usp=sharing

Thank you, @suonbo , but in this location I can only see the .jpg images (and they are cropped tables, not whole pages). I am looking for example with data required in the inference example:

python main.py --mode eval --data_type structure --config_file structure_config.json --data_root_dir /path/to/pascal_voc_structure_data --model_load_path /path/to/structure_model --table_words_dir /path/to/json_table_words_data

specifically, I need the config file (not in the repo!), pascal_voc_structure, table_words_dir (what's there?), json_table_words_data ...

[Danferno]

To anyone interested, I uploaded an example of the table structure recognition files here. It holds the annotation (pascal voc), the words (json) and the table image (.jpg)

[mineshmathew]

Has anyone figured how to run table detection alone ?

[Danferno]

Has anyone figured how to run table detection alone ?

NielsRogge made a notebook with examples

[muneeb2001]

NielsRogge made a notebook with examples

Can you share some tutorial where the table is converted to csv or html?

[nuocheng]

Has anyone figured how to run table detection alone ?

NielsRogge made a notebook with examples

Hello, thank you for providing a simple case study.
I encountered an issue while running jupyter notebook. There is a dependency on resnet18 in the Microsoft/table transformer detection configuration, but I failed to download using the third-party Python library timm. Do you have any method to make table transformer detection load the local resnet18 configuration?

[NielsRogge]

Hi,

See #158 with updated notebooks and demos