Commit 320316bd authored by Sabyasachi Mondal's avatar Sabyasachi Mondal
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Update README.md

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#### Group4: Sabyasachi Mondal , Ravi Yadav
fpga for streamlining of computation intensive tasks. Like in cases where signals or images from sensors are procesed continously.
### I Have tried to implementation from scratch with no libraries in use so we can have much higher control over design. It has been sucessful and for very large images received as continous streams FPGA is 3 times as fast as CPU.
#### I Have tried to implement this from scratch to have much higher control over design. It has been sucessful and for very large images received as continous streams FPGA is 3 times as fast as CPU.
| Index | Title | Content |
| - | ------ | ------ |
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![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")
## 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>
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![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 is summarized in the following:
### 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).
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>
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)
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