I initially started with the SSD-MobileNet-V1 model because my local machine(laptop) configurations is lower and I am training my dataset on CPU (no GPU). Some models (such as the SSD-MobileNet model) have an architecture that allows for faster detection but with less accuracy, while some models (such as the Faster-RCNN model) give slower detection but with more accuracy. TensorFlow provides several object detection models (pre-trained classifiers with specific neural network architectures) in its model zoo. Download the ssd_mobilenet_v1_coco model from TensorFlow's model zoo If portions of this tutorial do not work, it may be necessary to download and use this exact commit rather than the most up-to-date version.) 2b. (Note, this tutorial was done using this GitHub commit of the TensorFlow Object Detection API. ![]() Open the downloaded zip file and extract the “models-master” folder directly into the C:\tensorflow1 directory you just created. This working directory will contain the full TensorFlow object detection framework, as well as your training images, training data, trained classifier, configuration files, and everything else needed for the object detection classifier.ĭownload the full TensorFlow object detection repository located at by clicking the “Clone or Download” button and downloading the zip file. Download TensorFlow Object Detection API repository from GitHubĬreate a folder directly in C: and name it “tensorflow1”. It is fairly meticulous, but follow the instructions closely, because improper setup can cause unwieldy errors down the road. This portion of the tutorial goes over the full set up required. It also requires several additional Python packages, specific additions to the PATH and PYTHONPATH variables, and a few extra setup commands to get everything set up to run or train an object detection model. The TensorFlow Object Detection API requires using the specific directory structure provided in its GitHub repository. Set up TensorFlow Directory and Anaconda Virtual Environment The object detection repository itself also has installation instructions. Visit TensorFlow's website for further installation details, including how to install it on other operating systems (like Linux). As future versions of TensorFlow are released, you will likely need to continue updating the CUDA and cuDNN versions to the latest supported version.īe sure to install Anaconda with Python 3.6 as instructed in the video, as the Anaconda virtual environment will be used for the rest of this tutorial. Download and install CUDA v9.0 and cuDNN v7.0 (rather than CUDA v8.0 and cuDNN v6.0 as instructed in the video), because they are supported by TensorFlow-GPU v1.5. The video is made for TensorFlow-GPU v1.4, but the “pip install -upgrade tensorflow-gpu or pip install -upgrade tensorflow (FOR CPU)” command will automatically download version 1.5. Install TensorFlow-GPU and CPU by following the instructions or you can follow YouTube Video by Mark Jay. Install TensorFlow (skip this step if TensorFlow-GPU 1.5 is already installed) or TensorFlow-CPU If you encounter any problems while doing this project please do refer the link given below for the solutions Steps 1. Special Thanks To: EdjeElectronics, Sentdex The general procedure can also be used for Linux operating systems, but file paths and package installation commands will need to change accordingly. The tutorial is written for Windows 10, and it will also work for Windows 7 and 8. So, it is very necessary to set up a database for plant protection We believe that the first step is to teach a computer how to classify plants. The urgent situation is that many plants are at the risk of extinction. So, the diverseness of the plant community should be restored and put everything back to balance. It is one of the biggest duties of human beings to save the plants from various dangers. Regrettably, the amazing development of human civilization has disturbed this balance to a greater extent than realized. In addition, plants are important means of circumstances and production of human beings. ![]() The relationship between human beings and plants are also very close. Many of them carry significant information for the development of human society. ![]() Plants exist everywhere we live, as well as places without us. Plant identification based on leaf structure Introduction
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