Real-time-object-detection | Realtime Object Detection with deep neural network | Machine Learning library

I'm using a laptop with GPU 0: Intel(R) HD Graphics 630 and GPU 1: GTX1050 TI. I just finished setting up YOLO environment in Anaconda Environment using the following tutorial: https://appliedmachinelearning.blog/2018/05/27/running-yolo-v2-for-real-time-object-detection-on-videos-images-via-darkflow/

The problem is: whenever I try to render a video with YOLO in Anaconda environment using GPU

I followed this tutorial: https://www.pyimagesearch.com/2017/09/11/object-detection-with-deep-learning-and-opencv/ I changed this part where I converted the image feed to grayscale before inserting it to the neural network

I was trying to implement the example given in the blog (found here) for real time object detection using spring cloud data flow but could not download / find the image-viewer sink app as mentioned in the blog which super imposes the image with object detection done using tensorflow.

I am trying to bulk import applications from below bit.ly URL : bit.ly/Darwin-SR1-stream-applications-kafka-maven

Any help appreciated.

I would like create my own deep neural network model. I would like use a python script to detect specific object.

It is possible to create my own caffemodel file (or other model file) using python or c++ with a set of pictures ?

Do you have any research or tracks ?

For example, I would like create simylary programm like this project, but with my own deep neural image network without image-net neural pictures network:

I've been struggling trying to find a solution to this problem, and it may be simpler than I'm thinking.

I'm currently building an app that needs to analyze an image using TensorFlow. That part I've been able to get up and working no problem (think the "not a hotdog" app).

The problem I'm running into is that the image I need to analyze is going to contain several of the individual images I'm after.

TLDR; The best way I can think to explain, is that I have trained a model to analyze an individual egg. Now I take a picture of an egg carton (somewhat symmetrical, and orderly, but could be different angles/lighting/etc.) How would I got about extracting the individual eggs from the picture to analyze individually? The other key piece is that I need them ordered (top to bottom, or bottom to top, NOT by best match if, for example, using the OpenCV matchTemplate method)

I would love to share code, but so far it's all been research, which is what led me to OpenCV, and so far I've only added it as a library dependancy. I've looked at template matching, flood filling, etc. I just can't tie it all together to be able to "cut up" the image into it's individual pieces.

I hope this is enough to go off of, but please let me know and I can try to add more detail.

As a reference I've read through these examples:

https://samwize.com/2013/06/09/using-opencv-to-match-template-multiple-times/

https://www.toptal.com/machine-learning/real-time-object-detection-using-mser-in-ios ...and numerous others, these ones just seemed the most relevant to what I'm trying to accomplish.

EDIT As an example, I found this image that provides a good comparison to what I'll be working with. Given this image of lego blocks, how would I export the individual pieces? I'm not too concerned with extra data (i.e. doesn't need to crop it exactly, just need to separate the pieces). The other key thing is that I need them ordered from top to bottom (in the example image the blue block would be #1, red #2, etc.)

I have use codes from this link and sucessfully done the detection but the problem is it is only from webcam. I tried to modify the code so that it can read from file. the part I have modified is : I have written this