TorchSig v0.5.1

1. Massive dataset generation performance improvement utilizing multiprocessing. 10X faster dataset generation when using > 32 workers.
2. Improves resampling accuracy and reduction artifacts, reducing sidelobe levels from nominally -60 dB to about -90 dB
3. utils/dsp.py convolve now discards transition regions from filter output
4. Randomization rework: now allows parameters to be randomized internally per-process, therefore each signal generated is randomized rather than groups of signals having consistent values
5. Better implementation of FSK modulation using polyphase filter bank.
6. Initial release of image dataset. It is a wideband synthetic spectrogram dataset that mixes spectrogram images and image processing to build realistic looking spectrogram images with YOLO formatted labels. It includes image generators, image extractors, and image DSP based transforms.

@pvallance, @MattCarrickPL