vedanshu anshkumar

## aes256.cpp
#include <iostream>
#include <sstream>
#include <string>
#include <vector>
#include <memory>
#include <stdexcept>
#include <cstring>

#include <openssl/aes.h>
#include <openssl/err.h>

## EfficientDet Pytorch-lightning with EfficientNet v2 backbone Blog Post.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                anshkumar
                / EfficientDet Pytorch-lightning with EfficientNet v2 backbone Blog Post.ipynb
            
            
              Created
              June 21, 2022 05:02
                — forked from Chris-hughes10/EfficientDet Pytorch-lightning with EfficientNet v2 backbone Blog Post.ipynb
            
              
                EfficientDet Pytorch-lightning with EfficientNet v2 backbone Blog Post.ipynb
              
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## video_udp.py
#!/usr/bin/env python

import cv2
import gi
import numpy as np

gi.require_version('Gst', '1.0')
from gi.repository import Gst


## Mask-RCNN
name: "RESNET_Mask-RCNN"

input: "data"
input_dim: 1
input_dim: 3
input_dim: 224
input_dim: 224

input: "rois"
input_dim: 1 # to be changed on-the-fly to num ROIs

## faster-rcnn-vgg16-test.prototxt
name: "Faster R-CNN vgg16"

input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 224
  dim: 224
}
	#include <iostream>
	#include <sstream>
	#include <string>
	#include <vector>
	#include <memory>
	#include <stdexcept>
	#include <cstring>

	#include <openssl/aes.h>
	#include <openssl/err.h>
	#!/usr/bin/env python

	import cv2
	import gi
	import numpy as np

	gi.require_version('Gst', '1.0')
	from gi.repository import Gst
	name: "RESNET_Mask-RCNN"

	input: "data"
	input_dim: 1
	input_dim: 3
	input_dim: 224
	input_dim: 224

	input: "rois"
	input_dim: 1 # to be changed on-the-fly to num ROIs
	name: "Faster R-CNN vgg16"

	input: "data"
	input_shape {
	dim: 1
	dim: 3
	dim: 224
	dim: 224
	}