X393
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Usb_c_industrial_camera_fpga_usb3 | 610 | 6 months ago | 1 | Verilog | ||||||
| Source and Documentation files for USB C Industrial Camera Project, This repo contains PCB boards, FPGA , Camera and USB along with FPGA Firmware and USB Controller Firmware source. | ||||||||||
| C5soc_opencl | 65 | 3 years ago | 8 | apache-2.0 | Verilog | |||||
| DE1SOC DE10-NANO DE10-Standard OpenCL hardware that support VGA and desktop. And Some applications such as usb camera YUYV to RGB , Sobel and so on. | ||||||||||
| X393 | 26 | 5 years ago | gpl-3.0 | Verilog | ||||||
| mirror of https://git.elphel.com/Elphel/x393 | ||||||||||
| Csirx | 25 | 5 years ago | lgpl-3.0 | Verilog | ||||||
| Open-source CSI-2 receiver for Xilinx UltraScale parts | ||||||||||
| Eddr3 | 23 | 7 years ago | Verilog | |||||||
| mirror of https://git.elphel.com/Elphel/eddr3 | ||||||||||
| Ov7670 Verilog | 23 | 6 years ago | Verilog | |||||||
| Verilog modules required to get the OV7670 camera working | ||||||||||
| Fpga Stereo Camera Basys3 | 22 | a year ago | Verilog | |||||||
| Integration of two camera modules to Basys 3 FPGA | ||||||||||
| Upduino Ov7670 Camera | 17 | 6 years ago | 1 | Verilog | ||||||
| Design to connect Lattice Ultraplus FPGA to OV7670 Camera Module | ||||||||||
| Fpga Ov2640 | 17 | 3 years ago | 2 | mit | VHDL | |||||
| This project uses verilog to implement interaction with OV2640 camera, Bluetooth slave module and VGA display on FPGA. | ||||||||||
| Posture_recognition_cnn | 14 | 6 years ago | gpl-3.0 | Verilog | ||||||
| To help machines learn what we human beings are doing via a camera is important. Once it comes true, machines can make different responses to all kinds of human's postures. But the process is very difficult as well, because usually it is very slow and power-consuming, and requires a very large memory space. Here we focus on real-time posture recognition, and try to make the machine "know" what posture we make. The posture recognition system is consisted of DE10-Nano SoC FPGA Kit, a camera, and an HDMI monitor. SoC FPGA captures video streams from the camera, recognizes human postures with a CNN model, and finally shows the original video and classification result (standing, walking, waving, etc.) via HDMI interface. | ||||||||||
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