CSE_course_RAG / data /scratch /slide_012_prep_res.json
hatakekksheeshh's picture
Upload folder using huggingface_hub
7ec75e2 verified
{
"input_path": "/tmp/slide_012_prep.png",
"page_index": null,
"model_settings": {
"use_doc_preprocessor": true,
"use_textline_orientation": false
},
"doc_preprocessor_res": {
"input_path": null,
"page_index": null,
"model_settings": {
"use_doc_orientation_classify": false,
"use_doc_unwarping": false
},
"angle": -1
},
"dt_polys": [
[
[
33,
30
],
[
480,
32
],
[
480,
57
],
[
33,
56
]
],
[
[
1325,
36
],
[
1349,
36
],
[
1349,
53
],
[
1325,
53
]
],
[
[
89,
284
],
[
660,
287
],
[
660,
312
],
[
89,
309
]
],
[
[
119,
351
],
[
1277,
353
],
[
1277,
378
],
[
119,
376
]
],
[
[
148,
394
],
[
301,
394
],
[
301,
418
],
[
148,
418
]
],
[
[
118,
443
],
[
1295,
444
],
[
1295,
471
],
[
118,
470
]
],
[
[
147,
485
],
[
1030,
488
],
[
1030,
515
],
[
147,
513
]
],
[
[
120,
537
],
[
1281,
538
],
[
1281,
563
],
[
120,
562
]
],
[
[
147,
579
],
[
512,
580
],
[
512,
607
],
[
147,
606
]
],
[
[
49,
760
],
[
507,
761
],
[
507,
775
],
[
49,
774
]
],
[
[
767,
758
],
[
867,
760
],
[
867,
778
],
[
766,
776
]
],
[
[
1125,
759
],
[
1172,
759
],
[
1172,
777
],
[
1125,
777
]
]
],
"text_det_params": {
"limit_side_len": 64,
"limit_type": "min",
"thresh": 0.3,
"max_side_limit": 4000,
"box_thresh": 0.6,
"unclip_ratio": 1.5
},
"text_type": "general",
"textline_orientation_angles": [
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1,
-1
],
"text_rec_score_thresh": 0.0,
"return_word_box": false,
"rec_texts": [
"Recurrent Neural Networks",
"BK",
"Some examples of important design patterns:",
" RNNs that produce an output at each time step and have recurrent connections between",
"hidden units",
". RNNs that produce an output at each time step and have recurrent connections only from",
"the output at one time step to the hidden units at the next time step",
" RNNs with recurrent connections between hidden units, that read an entire sequence and",
"then produce a single output",
"Lecturer:Duc Dung Nguyen,PhD.Contact: nddung@hcmut.edu.vn",
"Deep Learning",
"9/47"
],
"rec_scores": [
0.9967246055603027,
0.9931349754333496,
0.9976677894592285,
0.9847972393035889,
0.9942428469657898,
0.9837331175804138,
0.9884930849075317,
0.9835271835327148,
0.9936838150024414,
0.9565293192863464,
0.9649302959442139,
0.9930726289749146
],
"rec_polys": [
[
[
33,
30
],
[
480,
32
],
[
480,
57
],
[
33,
56
]
],
[
[
1325,
36
],
[
1349,
36
],
[
1349,
53
],
[
1325,
53
]
],
[
[
89,
284
],
[
660,
287
],
[
660,
312
],
[
89,
309
]
],
[
[
119,
351
],
[
1277,
353
],
[
1277,
378
],
[
119,
376
]
],
[
[
148,
394
],
[
301,
394
],
[
301,
418
],
[
148,
418
]
],
[
[
118,
443
],
[
1295,
444
],
[
1295,
471
],
[
118,
470
]
],
[
[
147,
485
],
[
1030,
488
],
[
1030,
515
],
[
147,
513
]
],
[
[
120,
537
],
[
1281,
538
],
[
1281,
563
],
[
120,
562
]
],
[
[
147,
579
],
[
512,
580
],
[
512,
607
],
[
147,
606
]
],
[
[
49,
760
],
[
507,
761
],
[
507,
775
],
[
49,
774
]
],
[
[
767,
758
],
[
867,
760
],
[
867,
778
],
[
766,
776
]
],
[
[
1125,
759
],
[
1172,
759
],
[
1172,
777
],
[
1125,
777
]
]
],
"rec_boxes": [
[
33,
30,
480,
57
],
[
1325,
36,
1349,
53
],
[
89,
284,
660,
312
],
[
119,
351,
1277,
378
],
[
148,
394,
301,
418
],
[
118,
443,
1295,
471
],
[
147,
485,
1030,
515
],
[
120,
537,
1281,
563
],
[
147,
579,
512,
607
],
[
49,
760,
507,
775
],
[
766,
758,
867,
778
],
[
1125,
759,
1172,
777
]
]
}