docs: add crnn_mobilenet_v3_large performances in doc (TF)

[charlesmindee]

This PR adds the benchmark results for crnn_mobilenet_v3_large in the doc on the tensorflow backend.

Here are the pytorch results:

FUNSD
Model Evaluation (model= db_resnet50 + crnn_mobilenet_v3_large, dataset=FUNSD)
Text Detection - Recall: 79.99%, Precision: 87.22%, Mean IoU: 71.29%
Text Recognition - Accuracy: 86.65% (unicase: 87.40%)
OCR - Recall: 68.90% (unicase: 69.37%), Precision: 75.13% (unicase: 75.64%), Mean IoU: 71.29%

CORD
Model Evaluation (model= db_resnet50 + crnn_mobilenet_v3_large, dataset=CORD)
Text Detection - Recall: 93.00%, Precision: 91.37%, Mean IoU: 76.68%
Text Recognition - Accuracy: 92.71% (unicase: 93.16%)
OCR - Recall: 84.82% (unicase: 85.23%), Precision: 83.33% (unicase: 83.74%), Mean IoU: 76.68%

FORM US
Model Evaluation (model= db_resnet50 + crnn_mobilenet_v3_large, dataset=OCRDataset)
Text Detection - Recall: 77.55%, Precision: 91.22%, Mean IoU: 70.77%
Text Recognition - Accuracy: 84.46% (unicase: 85.07%)
OCR - Recall: 75.34% (unicase: 75.62%), Precision: 88.63% (unicase: 88.96%), Mean IoU: 70.77%

IDS
Model Evaluation (model= db_resnet50 + crnn_mobilenet_v3_large, dataset=OCRDataset)
Text Detection - Recall: 69.46%, Precision: 74.21%, Mean IoU: 61.29%
Text Recognition - Accuracy: 66.30% (unicase: 69.53%)
OCR - Recall: 47.32% (unicase: 50.65%), Precision: 50.56% (unicase: 54.12%), Mean IoU: 61.29%

RECEIPTS
Model Evaluation (model= db_resnet50 + crnn_mobilenet_v3_large, dataset=OCRDataset)
Text Detection - Recall: 86.04%, Precision: 89.94%, Mean IoU: 76.12%
Text Recognition - Accuracy: 91.89% (unicase: 92.70%)
OCR - Recall: 78.35% (unicase: 79.08%), Precision: 81.90% (unicase: 82.66%), Mean IoU: 76.12%

INVOICES
Text Detection - Recall: 68.28%, Precision: 72.05%, Mean IoU: 62.69%
Text Recognition - Accuracy: 90.76% (unicase: 92.27%)
OCR - Recall: 62.09% (unicase: 62.99%), Precision: 65.52% (unicase: 66.47%), Mean IoU: 62.69%

ROAD FINES
Model Evaluation (model= db_resnet50 + crnn_mobilenet_v3_large, dataset=OCRDataset)
Text Detection - Recall: 92.34%, Precision: 90.72%, Mean IoU: 83.86%
Text Recognition - Accuracy: 94.72% (unicase: 95.72%)
OCR - Recall: 86.18% (unicase: 86.94%), Precision: 84.67% (unicase: 85.42%), Mean IoU: 83.86%

RESUMES
Model Evaluation (model= db_resnet50 + crnn_mobilenet_v3_large, dataset=OCRDataset)
Text Detection - Recall: 91.49%, Precision: 94.42%, Mean IoU: 86.93%
Text Recognition - Accuracy: 92.89% (unicase: 94.22%)
OCR - Recall: 84.31% (unicase: 85.40%), Precision: 87.00% (unicase: 88.13%), Mean IoU: 86.93%

[fg-mindee]

Nice results!