Fix issue #132, #127, #126, #124, #123, #122, #118 and #61 + We have improved the accuracy for the detector. - Now we detect motorcycles in addition to cars - You'll have fewer false positives on cars without plates. - The bounding boxes on overlapping cars are more accurate. + We have improved the accuracy for the Pyramidal search. The bounding boxes on far away or small the cars and plates are tighter. + We have improved the accuracy for Vehicle Body Style Recognition (VBSR) and added 'motorcycle' to the classes. + We have improved the accuracy for Vehicle Color Recognition (VCR). + Completely redesigned License Plate Country Identification (LPCI). + Return "frame_id" in every callback when parallel mode is enabled to ease matching the input to the result. + Now it's possible to attach the license to a Microsoft Azure VM instead of hardware to avoid requiring a dedicated server. More info at https://github.com/DoubangoTelecom/ultimateALPR-SDK/blob/master/AWS.md#azure + Now we return the OCR score for each character/digit in the license plate. More info about the JSON 'confidences' field at https://www.doubango.org/SDKs/anpr/docs/Frequently_Asked_Questions_(FAQ).html#could-you-explain-what-each-field-in-the-json-result-mean. This is backward compatible, no change needed in your code.

Improve car/plate detectors accuracy to reduce false-positives on cars with no plate #118

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