ImageAI | python library built to empower developers

by OlafenwaMoses Python Version: Current License: MIT

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A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

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ImageAI Key Features

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ImageAI Examples and Code Snippets

CarTeller

Python

Lines of Code : 33

License : No License

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 主要作者：wqx
      五个功能界面，个人信息界面，历史界面以及其功能。接口文档微调。
      登录功能，滑块检测功能，界面弹窗效果。
 协作者：cj
      登录界面，API界面及部分调整

作者：cjj
	登录、注册界面，tab滑动切换Fragments，从手机存储读取照片，基于okHttp框架的以Json为载体的数据传输和解析逻辑
	，通过http协议与服务器交互进行几种车辆识别。

  服务器端：
  flask文件内内容,主要作者：gxk （flask+gunicorn

Fire Arm and Person Detection Using ImageAI,Run the program

Python

Lines of Code : 1

License : No License

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python3 detector.py

DogSpotting,Install

HTML

Lines of Code : 1

License : No License

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docker-compose up --build -d

ImageAI - video analysis per second

Python

Lines of Code : 36

License : Permissive (MIT License)

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from imageai.Detection import VideoObjectDetection
import os
from matplotlib import pyplot as plt


execution_path = os.getcwd()

color_index = {'bus': 'red', 'handbag': 'steelblue', 'giraffe': 'orange', 'spoon': 'gray', 'cup': 'yellow', 'chair': 'gr

ImageAI - video analysis per frame

Python

Lines of Code : 36

License : Permissive (MIT License)

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from imageai.Detection import VideoObjectDetection
import os
from matplotlib import pyplot as plt


execution_path = os.getcwd()

color_index = {'bus': 'red', 'handbag': 'steelblue', 'giraffe': 'orange', 'spoon': 'gray', 'cup': 'yellow', 'chair': 'gr

ImageAI - custom detection from array extract objects array

Python

Lines of Code : 18

License : Permissive (MIT License)

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from imageai.Detection.Custom import CustomObjectDetection
import cv2

image_array = cv2.imread("holo2.jpg")

detector = CustomObjectDetection()
detector.setModelTypeAsYOLOv3()
detector.setModelPath("yolov3_hololens-yolo_mAP-0.82726_epoch-73.pt") # h

Could not load dynamic library 'libcudnn.so.8'

Python

Lines of Code : 17

License : Strong Copyleft (CC BY-SA 4.0)

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gediz@u18serv:~$  ls /usr/local |grep cuda
cuda
cuda-11
cuda-11.5

gediz@u18serv:~$ ls /usr/local/cuda-11.5/lib64/libcudnn.so.8*
/usr/local/cuda-11.5/lib64/libcudnn.so.8  /usr/local/cuda-11.5/lib64/libcudnn.so.8.2.4

Tensorflow conflict in ImageAI pipeline

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

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pip install imageai --upgrade

Cannot import name '_imaging' from 'PIL'

Python

Lines of Code : 4

License : Strong Copyleft (CC BY-SA 4.0)

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pip uninstall PIL
pip uninstall Pillow
pip install Pillow

i have a error when im using imageai package to do custom product detection

Python

Lines of Code : 6

License : Strong Copyleft (CC BY-SA 4.0)

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from imageai.Prediction.Custom import ModelTraining
    model_trainer = ModelTraining()
    model_trainer.setModelTypeAsResNet()
    model_trainer.setDataDirectory(r"C:\Users\User\Desktop\directory\Copy of shopee-product-detection-dataset"

Community Discussions

Trending Discussions on ImageAI

MyImage.Source index is not changing with the list

Could not load dynamic library 'libcudnn.so.8'

Tensorflow conflict in ImageAI pipeline

How can I run ImageAI on my GPU and not my CPU

Are there preconfigured libraries for video object recognition, in which I could pass in an mp4 into a function

How to detect an object real time and track it automatically, instead of user having to draw a bounding box around the object to be tracked?

Little to No GPU Usage during Custom Object Detection Training After Recent ImageAI Update

object detection with imageai -module 'keras.backend' has no attribute 'get_session'-

object detection using imageAI

ImageAI/Keras can't read ResNet model on Raspberry Pi but works on Windows

QUESTION

MyImage.Source index is not changing with the list

Asked 2021-Nov-08 at 11:42

Could someone help me with an index issue. The line for MyImage.Source was added and it does not seem to be updating the images in the list. The text is updaing just fine. How do I get the index from GrapplingGuard[ndx].ImageA to update the image?

Originally the GrapplingGuard[ndx].ImageA was GrapplingGuard[0] however I assume that I need to indicate that it should relate to [ndx]. ImageAI have tried to move the line after the Binding Context but that did not change anything. Do I need to include something in the OnButtonClicked section?

...

ANSWER

Answered 2021-Nov-08 at 11:42

I found the solution, I had to add the MyImage.Source line in the incrementing section

Source https://stackoverflow.com/questions/69500279

QUESTION

Could not load dynamic library 'libcudnn.so.8'

Asked 2021-Oct-29 at 04:16

I'm using cuda 11.0, with cudnn 8.0.5, tensorflow 2.4 the error I got from runnning my code was this,

...

ANSWER

Answered 2021-Oct-29 at 04:16

Check CUDA folders:

Source https://stackoverflow.com/questions/69750970

QUESTION

Tensorflow conflict in ImageAI pipeline

Asked 2021-Oct-28 at 11:39

As a Python 3.9.7 user, I created an environment which has:tensorflow-gpu==2.6.0, keras==2.6.0 and also using imageai, however, whenever I run the code, I get the error:

...

ANSWER

Answered 2021-Oct-28 at 11:39

Ok, so what managed to solve the dependency conflict was - after installing all requirements, I updated imageai with:

Source https://stackoverflow.com/questions/69740243

QUESTION

How can I run ImageAI on my GPU and not my CPU

Asked 2021-Oct-06 at 13:58

So I am quite new to this I was trying to find answers on google but it is kind of not working. So I am trying to run this library ImageAI library

I am able to run it normally on the CPU at least I think it runs on CPU by just calling python test.py. Am I correct there

But since the model prediction takes a long time I would like to run it on my GPU. What I was trying to do is create a conda environment and activate it but after I do I get this error.

ModuleNotFoundError: No module named 'imageai.Classification'

Although I have imageai installed in my environment

...

ANSWER

Answered 2021-Oct-06 at 13:58

I found the solution it doesnt require the conda environment. ImageAI automatically runs on GPU if available. All you need to do is to ensure you have the GPU version of Tensorflow installed.

Source https://stackoverflow.com/questions/69466122

QUESTION

Are there preconfigured libraries for video object recognition, in which I could pass in an mp4 into a function

Asked 2021-Sep-04 at 21:26

I have a video of me walking down a city street, can I pass that into a function that will then print what it sees (telephone pole, trash can, dog, ..ect)? What library could I use?

The key is I dont want to have to train the model (ie pass in a bunch of photos of trach cans or dogs ect)

(ideally python)

SOLVED This article works great actually

https://towardsdatascience.com/how-to-create-a-simple-object-detection-system-with-python-and-imageai-ee1bcaf6b111

...

ANSWER

Answered 2021-Sep-04 at 19:13

yes there are possibilities to do object detection in real time. For instance, YOLO in combination with darknet would maybe be a possibility to for you. For more information see: https://pjreddie.com/darknet/yolo/ and https://github.com/pjreddie/darknet/wiki/YOLO:-Real-Time-Object-Detection

Source https://stackoverflow.com/questions/69058226

QUESTION

How to detect an object real time and track it automatically, instead of user having to draw a bounding box around the object to be tracked?

Asked 2021-Feb-09 at 02:08

I have the following code where the user can press p to pause the video, draw a bounding box around the object to be tracked, and then press Enter (carriage return) to track that object in the video feed:

...

ANSWER

Answered 2021-Feb-08 at 05:59

I want to answer this question with the help of this article which I also used before and met the similar problem with yours. Here are the suggestions:

Run YOLOv3 with darknet framework which will increase the performance.
In your code snippet, it looks it doesn't let you to decide network input width and height so I don't know what you are using for them. Decreasing network width and height will increase the speed but oppositely decrease the accuracy.
YOLOv3 trained for 80 objects but you only need some of them. I also only needed the cars in my project before. Unfortunately, you can't manipulate the weight file which is already trained and also you can not train your objects such well.
The other way I also tried before is that I transfered YOLOv3 to another thread and I also didnt apply yolo to all frames. I only applied some of them, for example: 1 frame of each 10 frame. This was also helpful for me.
Or you can choose a better cpu pc :)

Source https://stackoverflow.com/questions/66096223

QUESTION

Little to No GPU Usage during Custom Object Detection Training After Recent ImageAI Update

Asked 2021-Jan-10 at 14:49

I have trained a custom object detection model using 750 images using ImageAI on Google Colab Pro about a month ago using TensorFlowGPU 1.13 and have roughly 30min/epoch training time. Now, when I train using the same dataset but with TensorFlowGPU 2.4.3 (ImageAI doesnt support old TF anymore), I am getting very little GPU usage (0.1GB) and 6 hour per epoch training times. I have tried training the same model on my local machine and I am getting very slow training times as well.

I am using the following imports (based on ImageAI documentation):

!pip install tensorflow-gpu==2.4.0 keras==2.4.3 numpy==1.19.3 pillow==7.0.0 scipy==1.4.1 h5py==2.10.0 matplotlib==3.3.2 opencv-python keras-resnet==0.2.0 !pip install imageai --upgrade

I am pulling my training data from Google Drive.

Is there anything I could be missing that could speed up my object detection training times on either Google Colab or my local machine? The slow training times is slowing my research down.

...

ANSWER

Answered 2021-Jan-10 at 14:49

If you want full GPU usage, from my experience, you must revert back to previous versions of ImageAI and it's compatible packages. Here is a list of compatible packages that I have installed that work as of now (January 2021) on my local machine and Google Colab:

TF-GPU==1.13.1
Keras==2.2.4
Imageai==2.1.0

This fixed any issue caused by the most recent patch of ImageAI. I now am back to full GPU usage. Until the issue is patched, I suggest using the old version.

Source https://stackoverflow.com/questions/65632510

QUESTION

object detection with imageai -module 'keras.backend' has no attribute 'get_session'-

Asked 2020-Dec-02 at 00:12

I have the following code

...

ANSWER

Answered 2020-Dec-02 at 00:12

You are using https://github.com/OlafenwaMoses/ImageAI.
Despite it is not deprecated, the last commit from this repository is from January 2019.
Also, they integrate in their framework outdated networks
( keras-retinanet is deprecated, for instance )

Given that, I will answer your last question:
'is there any other way to use pre-trained object detection models?':

Yes, there are.
Both tensorflow and pytorch,
that are currently the main libraries for deep learning, offer them.

For instance, pytorch has few detection models coded in torchvision.models.detection : https://github.com/pytorch/vision/tree/master/torchvision/models/detection

Note 1: to install pytorch, you have to run in your conda environment:
conda install torchvision -c pytorch

Note 2: the following code has been made functional, combining the docstrings in : https://github.com/pytorch/vision/blob/master/torchvision/models/detection/retinanet.py
and this tutorial:
https://debuggercafe.com/faster-rcnn-object-detection-with-pytorch/
I suggest you to have a look at them, too.

Source https://stackoverflow.com/questions/65025949

QUESTION

object detection using imageAI

Asked 2020-Nov-18 at 14:25

I am working on a plant leaf detection model using imageAI library. when I create an instance of the model the following error occurs. I can not understand the error. this is my code:

...

ANSWER

Answered 2020-Nov-18 at 14:25

you have to use older version of keras and tensorflow.

try this

pip3 install tensorflow==1.13.1

pip3 install keras==2.2.4

or you can install tensorflow 1.14 or 1.15.1

Source https://stackoverflow.com/questions/64894824

QUESTION

ImageAI/Keras can't read ResNet model on Raspberry Pi but works on Windows

Asked 2020-Nov-11 at 07:48

About

I'm trying to load and use an ImageAI ResNet model and then access it via a Flask server. More details about the project are on my Github repository.

My code runs well on Windows but not on Linux. I cloned all of my files directly to a Raspberry Pi and then installed all the pip dependencies. However, the program breaks when initializing the Predictor class.

Steps taken

Installed the same pip version of every package as my Windows PC
Used virtualenv
Reinstalled Tensorflow from different wheels (not just pip)
Searched ImageAI's issues. There were several similar issues but no solutions that worked
Created an issue in the ImageAI repo; no response yet
Used a different Raspberry Pi (both Pi 2B and 3B)
Searched StackOverflow for Raspberry Pi Tensorflow issues. There are surprisingly many! However, installing different versions of Tensorflow didn't work. I couldn't find any other suggested solutions.
Used SHA-256 checksums to verify that all of my files were the exact same as my Windows PC

Once again, an identical version of this project works on my Windows PC. It's probably a Linux/Raspberry Pi package issue, right?

Code ...

ANSWER

Answered 2020-Nov-02 at 17:48

Well this is odd...

I fixed the issue by installing literally every package at the same version as my Windows machine.

Steps:

Create file dependencies.txt with the contents of the pip3 freeze Windows output
Run python3 -m pip install -r dependencies.txt. This forces pip to install literally every dependency at the same version.
Run the program with sudo python3 app.py

It seems like it was a package error after all.

Source https://stackoverflow.com/questions/64640117

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