Commit 8d844ff7 authored by Sabyasachi Mondal's avatar Sabyasachi Mondal
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Update README.md

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......@@ -88,26 +88,26 @@ https://mygit.th-deg.de/sm11312/fpga_final_project/-/blob/main/design_1.pdf
*It uses different weights in different pixel positions in a 2x2 cell which effectively acts like an differential operation. So places with higher differences in pixel values get pronounced in the output.*
![Introduction to Robert's cross operation](https://homepages.inf.ed.ac.uk/rbf/HIPR2/roberts.htm "Brief introduction to Robert's cross operation")
[Introduction to Robert's cross operation](https://homepages.inf.ed.ac.uk/rbf/HIPR2/roberts.htm "Brief introduction to Robert's cross operation")
![Output image](https://mygit.th-deg.de/sm11312/fpga_final_project/-/raw/main/Output.jpg "Output image with the terrain contours")
[Output image](https://mygit.th-deg.de/sm11312/fpga_final_project/-/raw/main/Output.jpg "Output image with the terrain contours")
## What we achieved and the caveat :
<b>*We intended to build a architechture that can process multiple streams and process them in same parallel level and we were sucessful.*</b>
<b>*Our main goal is to ensure such a architechture runs faster in FPGA and it was reasonably fast; most importantly it can be scaled up to handle multiple streams.*</b>
<b>*CPU Average for images was at about 25s and FPGA at about 10s for 6 images for smaller images*</b>
<b>*CPU Average for images was at about 25s and FPGA at about 10s for 6 images. For smaller images a comparison table is shown below:*</b>
![Speed comparison in single images](https://mygit.th-deg.de/sm11312/fpga_final_project/-/raw/main/Speed_table.JPG "Speed comparison in single images")
But the best part of the result was the FPGA speed increases when images are processed for longer time, larger images, larger streams of data.
#### An Important observation was that for very large images (greater then 1 MB) our resizer is almost 3 times faster, but its just about 0.2 times fast for lower size images seen in above table, (for different size image analysis graph linked below).
<b>*On some cases the FPGA took 11s and CPU took rougly thee times as much time 33s. In images of size range 800-1000 kB we achieve a 200 percent speed up, and around 20 percent for 200-300kB images.*<b>
<b>*An Important observation was that for very large images (greater then 1 MB) our resizer is almost 3 times faster, but its just about 0.2 times fast for lower size images seen in above table, (for different size image analysis graph linked below).*<b>
Please refer to the [Jupyter notebook linked here](https://mygit.th-deg.de/sm11312/fpga_final_project/-/blob/main/Notebook_Speed_Comparison.ipynb) which shows this result (image 2 and 3 are around 200KB rest are above 800KB)
<b>*On some cases the FPGA took 11s and CPU took rougly thee times as much time 33s. In images of size range 800-1000 kB we achieve a 200 percent speed up, and around 20 percent for 200-300kB images.*<b>
## Future scope
*This is a new idea and has no previous references except implementaton guides. All the code and ideas were developed groundup*
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