How could I test my own image to detect formula?

[f771216203]

I try to test my own image, but I don't know how to do it.
I try this code:
python3 test.py
--dataset_root ./
--trained_model AMATH512_e1GTDB.pth
--visual_threshold 0.25
--cuda True
--exp_name test_MATH512
--test_data ./ --suffix "_512"
--model_type 512 --cfg hboxes512
--padding 0 2
--kernel 1 5
--batch_size 8

If I want to test an image, what should I put in dataset_root and test_data ?

[jjdredd]

Maybe this could be helpful. It's running on cpu only though:

https://github.com/jjdredd/ScanSSD/blob/lowmem/detect.py

[f771216203]

@jjdredd thanks a lot!!! I success the test. But I found some code should be modified.

b[0] = int(o_box[0] * images.shape[0]) ==> b[0] = int(o_box[0] * images.shape[1])
b[1] = int(o_box[1] * images.shape[1]) ==> b[1] = int(o_box[1] * images.shape[0])
b[2] = int(o_box[2] * images.shape[0]) ==> b[2] = int(o_box[2] * images.shape[1])
b[3] = int(o_box[3] * images.shape[1]) ==> b[3] = int(o_box[3] * images.shape[0])

And the draw_box will be correct.

[TanayKarve]

Maybe this could be helpful. It's running on cpu only though:

https://github.com/jjdredd/ScanSSD/blob/lowmem/detect.py

In function _img_to_tensor I noticed that the image is being resized to (512,512)
But the paper states that a rolling window of 512 x 512 is being passed over the document image to prevent resizing. Won;t resizing the image affect results? As most of the document images aren't in 1:1 aspect ratio.

[jjdredd]

It's just a quick test script. Usually you would divide the image into parts, detect in each subimage and stich the bounding
boxes IIRC.

[ainouch]

@jjdredd thanks a lot!!! I success the test. But I found some code should be modified.

b[0] = int(o_box[0] * images.shape[0]) ==> b[0] = int(o_box[0] * images.shape[1])
b[1] = int(o_box[1] * images.shape[1]) ==> b[1] = int(o_box[1] * images.shape[0])
b[2] = int(o_box[2] * images.shape[0]) ==> b[2] = int(o_box[2] * images.shape[1])
b[3] = int(o_box[3] * images.shape[1]) ==> b[3] = int(o_box[3] * images.shape[0])

And the draw_box will be correct.

please can you explain me how you changed the code detect.py to detect formulas on your own images ?

[ainouch]

hello!
I ve tried to run ' detect.py' in conda virt env in which i ve installed pytorch cpu version.
It shows me the following error:

ScanSSD-master>python detect.py Traceback (most recent call last): File "detect.py", line 156, in md = MathDetector('AMATH512_e1GTDB.pth', ArgStub()) File "detect.py", line 96, in init net = build_ssd(args, 'test', config.exp_cfg[args.cfg], 0, args.model_type, 2) File "C:\Users\UM6P\Desktop\Anass D4-R projects\anass_formulas_recog_project\ScanSSD-master\ScanSSD-master\ssd.py", line 218, in build_ssd return SSD(args, phase, cfg, size, base_, extras_, head_, num_classes, gpu_id) File "C:\Users\UM6P\Desktop\Anass D4-R projects\anass_formulas_recog_project\ScanSSD-master\ScanSSD-master\ssd.py", line 38, in init self.priors.to(gpu_id) File "C:\Users\UM6P\anaconda3\envs\Object_Detection_PyTorch_SSD300_VGG16_Backbone\lib\site-packages\torch\cuda_init_.py", line 186, in _lazy_init check_driver() File "C:\Users\UM6P\anaconda3\envs\Object_Detection_PyTorch_SSD300_VGG16_Backbone\lib\site-packages\torch\cuda_init.py", line 61, in _check_driver raise AssertionError("Torch not compiled with CUDA enabled") AssertionError: Torch not compiled with CUDA enabled

help me please !!

[AaaJrwp4]

Hey @jjdredd ,
thank you so much for your code!
I am trying to use it and got an error.

Python 3.8
Cuda 11.7
Torch 1.10.0+cu111, Torchvision 0.11.0, Torchaudio 0.10.0

Traceback (most recent call last):  
 File "detect.py", line 163, in <module> 
b, s = md.DetectAny(0.2, a)    
 File "detect.py", line 147, in DetectAny 
boxes, scores = self.Detect(thres, t) 
 File "detect.py", line 114, in Detect  
y, debug_boxes, debug_scores = self._net(images)  # forward pass 
 File "/home/$user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl 
 return forward_call(*input, **kwargs)    
File "/home/$user/Repos/ScanSSD/ssd/ssd.py", line 108, in forward    
 output, boxes, scores = self.detect( 
File "/home/$user/.local/lib/python3.8/site-packages/torch/autograd/function.py", line 261, in __call__  

raise RuntimeError( 
 RuntimeError: Legacy autograd function with non-static forward method is deprecated.   
Please use new-style autograd function with static forward method.   
(Example: https://pytorch.org/docs/stable/autograd.html#torch.autograd.Function) 

Of course I have check out the link below, but I didn't know what change.
Can you or anybody else help me out ?

[jiboncom]

I made this Colab for custom image detection
https://colab.research.google.com/drive/1cE_Sv4TaFONAHuQxr-_Da2PbAceNniWW

Not very elegant, but it works. It does a rolling window through the image and fixes de boundary boxes to the complete image so you can use images of any size.