text: Title: Quality Issues
  Body: Hi there,
  
  Thank you for the amazing work. This library makes it so easy to perform OCR. However, it seems like the quality of the recognition results is not very good especially with app/web screenshots or rendered text. Detector also fails to detect single letters. Here are some of the failure cases:
  
  1. Detector failure of single letters:
  ![image](https://user-images.githubusercontent.com/11090613/121856797-5721c800-cd0e-11eb-9889-d0e909792576.png)
  
  2. Recognition failure of small time boxes (model=en): 
  ![image](https://user-images.githubusercontent.com/11090613/121856938-82a4b280-cd0e-11eb-8694-c25f2a40ea24.png)
  ![image](https://user-images.githubusercontent.com/11090613/121857178-c4355d80-cd0e-11eb-9626-a7a631ae6bad.png)
  ![image](https://user-images.githubusercontent.com/11090613/121857229-d57e6a00-cd0e-11eb-94e1-8490c2a9eb9f.png)
  ![image](https://user-images.githubusercontent.com/11090613/121857313-ec24c100-cd0e-11eb-9120-90926450bfd7.png)
  
  3. Bad results on symbols (model=en):
  ![image](https://user-images.githubusercontent.com/11090613/121857054-a23bdb00-cd0e-11eb-8a72-b25e16b9b729.png)
  
  4. Confusion between 0 and o (model=en):
  ![image](https://user-images.githubusercontent.com/11090613/121857599-3ad25b00-cd0f-11eb-9045-fe330fca32e3.png)
  
  5. Bad 'en' results on (model=en+ja):
  ![image](https://user-images.githubusercontent.com/11090613/121858057-a9171d80-cd0f-11eb-988b-2df39a5a76ba.png)
  ![image](https://user-images.githubusercontent.com/11090613/121858777-630e8980-cd10-11eb-8d6c-bc6e4a1b374e.png)
  ![image](https://user-images.githubusercontent.com/11090613/121858864-7ae60d80-cd10-11eb-8589-494abab2b275.png)
  ![image](https://user-images.githubusercontent.com/11090613/121858898-85a0a280-cd10-11eb-8766-34b55ed47e3d.png)
  ![image](https://user-images.githubusercontent.com/11090613/121859038-acf76f80-cd10-11eb-8d34-00d7c663bc18.png)
  ![image](https://user-images.githubusercontent.com/11090613/121859271-f051de00-cd10-11eb-92ca-91cce6b640fa.png)
  ![image](https://user-images.githubusercontent.com/11090613/121861164-06f93480-cd13-11eb-9c65-b9c614741148.png)
  ![image](https://user-images.githubusercontent.com/11090613/121861542-5475a180-cd13-11eb-835c-aa540679e92c.png)
  
  
  ## Extra Info:
  
  I am using the default settings (with batch_size=32) on image with scale (height=~800px & width=~400px). Is there any setting I can tweak to improve the results or will I have to train from scratch on my dataset?
  
  Best regards