Other OCR platforms provide OCR confidence sometimes per character and sometimes per word.
The confidence meaning how likely the result is to match the input image, for very poorly scanned documents where noise is a problem this can cause the current API to return incorrect text frequently with no programmatic way to detect if the result should be trusted or sent to a user for verification.
Having this as an optional query parameter on the API would be helpful, perhaps confidencePerWord=true and confidencePerCharacter=true11 votes
Only Recognize Text is currently containerised. As this API is deprecated, could we please get a container version of the newer Read API?1 vote
k4a_image_t depth_image = k4a_capture_get_depth_image(capture);
color_frame=cv::Mat(k4a_image_get_height_pixels(color_image), k4a_image_get_width_pixels(color_image), CV_8UC3, k4a_image_get_buffer(color_image));
The imshow here creates a 'segmentation fault' even though there are proper values in the matrix. I check this is not an opencv fault. Could someone please help to visualize color and depth data from custom application.1 vote
There is a little bug in the JSON response from the REST API:
In the JSON response, the color object contains two most-likely identical features with different names - "isBWImg" and "isBwImg" (lower-case "w" vs. capital "W").
API version: 2.0
Region: West Europe1 vote
Hello Azure Team,
Using azure online tool , the attached image generates the correct json response(all image text), but when we use it via computervision, cognitiveserive API in web or mobile Android it returns less/incorrect json response which is invalid and we cannot pick number from it.1 vote
Please see our product roadmap here: https://azure.microsoft.com/en-us/updates/.
Could it be possible to use this algorithm with a video stream instead of single images2 votes
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