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Douglas Daseeco
Douglas Daseeco
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If we seek proven working source code to plug into a GPLv2-licence compatible solution, we should at least consider autotrace. Its source code is open for review. It can be tested against the example images we have and, if it works fine, called by our GPLv2 software. We can even use the calling code in Inkscape's plug-in image tracing implementation as a good starting point for design and implementation of our calling program, whether it be C, C++, Java, Python, or ECMA (JS).

The trace algorithm in Adobe Illustrator is comparable but is not open source.

If we seek theory, there are several articles that resentacademic publications discussing some of the theory, the last being most aligned with machine learning ideology. But I would not dismiss the earlier work, since simply because it doesn't connect with the current machine learning idioms. Investigating what is fully implemented in the field and successfully used by many successfully. The business wisdom offollows a wise old is sometimes apropos and probabilistically correctbusiness proverb: The bird in the hand is often worth more than two in the bush.

Many of the online drawing programs collect data. It would not be surprising if, behind the gracious give-away of online bandwidth, they are establishing a continuously improving data set for training a new breed of autotracers. None have published AI designs admitting as much, but they would not be legally obligated to do so because a single input example is indeterminable from the autotrace service that could resulting from the training.

If we seek proven working source code to plug into a GPLv2-licence compatible solution, we should at least consider autotrace. Its source code is open for review. It can be tested against the example images we have and, if it works fine, called by our GPLv2 software. We can even use the calling code in Inkscape's plug-in image tracing implementation as a good starting point for design and implementation of our calling program, whether it be C, C++, Java, Python, or ECMA (JS).

If we seek theory, there are several articles that resent theory, the last being most aligned with machine learning ideology. But I would not dismiss the earlier work, since it is implemented in the field and used by many successfully. The business wisdom of old is sometimes apropos and probabilistically correct: The bird in the hand is often worth more than two in the bush.

If we seek proven working source code to plug into a GPLv2-licence compatible solution, we should at least consider autotrace. Its source code is open for review. It can be tested against the example images we have and, if it works fine, called by our GPLv2 software. We can even use the calling code in Inkscape's plug-in image tracing implementation as a good starting point for design and implementation of our calling program, whether it be C, C++, Java, Python, or ECMA (JS).

The trace algorithm in Adobe Illustrator is comparable but is not open source.

If we seek theory, there are several academic publications discussing some of the theory, the last being most aligned with machine learning ideology. I would not dismiss earlier work simply because it doesn't connect with the current machine learning idioms. Investigating what is fully implemented and successfully used by many follows a wise old business proverb: The bird in the hand is worth two in the bush.

Many of the online drawing programs collect data. It would not be surprising if, behind the gracious give-away of online bandwidth, they are establishing a continuously improving data set for training a new breed of autotracers. None have published AI designs admitting as much, but they would not be legally obligated to do so because a single input example is indeterminable from the autotrace service that could resulting from the training.

Source Link
Douglas Daseeco
Douglas Daseeco
  • 7.5k
  • 1
  • 27
  • 63

If we seek proven working source code to plug into a GPLv2-licence compatible solution, we should at least consider autotrace. Its source code is open for review. It can be tested against the example images we have and, if it works fine, called by our GPLv2 software. We can even use the calling code in Inkscape's plug-in image tracing implementation as a good starting point for design and implementation of our calling program, whether it be C, C++, Java, Python, or ECMA (JS).

If we seek theory, there are several articles that resent theory, the last being most aligned with machine learning ideology. But I would not dismiss the earlier work, since it is implemented in the field and used by many successfully. The business wisdom of old is sometimes apropos and probabilistically correct: The bird in the hand is often worth more than two in the bush.