In the previous two blogs, we discussed Object Detection for Image and Video, in this blog we’ll use ImageAI library for Object Detection -Webcam. Start by installing the library ImageAi. Download the pre-trained Yolo Model from below link: yolo.h5 100%[===================>] 237.17M 67.8MB/s in 3.5s 2019-01-22 03:00:01 (67.8 MB/s) – ‘yolo.h5’ saved [248686624/248686624] Let’s import the…
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In the previous blog, we discussed about the Object Detection using the ImageAi library, in this blog, we’ll discuss about the Object Detection-Video. Concept is the same, like we have to initialize the class of the for Video Object detection and then load the pre-trained model. ImageAi support RetinaNet, YOLOv3 and TinyYOLOv3. To start the…
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Object detection refers to the capability of systems to locate objects in an image or scene and identify each object. In the previous blog, we discussed high-level API Keras, in this blog we start working on Object Detection task. History of Object detection is well explained in below infographics. This information was downloaded from the…
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In the previous 67 blogs, we follow the book like Hands-on Machine Learning with Scikit-Learn and TensorFlow, in the blog, we’ll try to use Keras, A high-level API to implement the classic MNIST classification problem. Keras Keras is a high-level API to quickly build and train deep learning models. Keras is useful when you want…
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In the previous few blogs, we are discussing various Reinforcement Learning, in this blog let’s try to play Ms. Pac-Man game using Deep Q-Learning. We’ll use OpenAi gym environments to create Ms. Pac-Man . Below is the piece of code which will create the environment. We’ll use DQN to train our agent. Observation (obs) is nothing but…
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In the previous few blogs, we are discussing various RL examples, in this blog let’s try to use the FastAi library to perform the simple classification. First, let’s install the FastAi library. Since we are using the Google Colab, we can download the the kaggle json file from our private google drive using below code. Above code downloads…
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In the previous few blogs, we are discussing various Reinforcement Learning, in this blog let’s discuss about Deep Q-Networks. On the challenges of Q-Learning is that it does not work well with a large MPD problem where we have multiple actions and states. Consider a game which has a matrix of 25* 10 with each state has…
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In the previous few blogs, we are discussing various RL examples, in this blog let’s use the Reinforcement Learning to tackle BipedalWalker-v2 task. Let’s understand the task first, as per Gym documentation: Reward is given for moving forward, total 300+ points up to the far end. If the robot falls, it gets -100. Applying motor…
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In the last few blogs, we discussed Reinforcement learning and example, in this blog we discuss another RL-Cart-Pole Task. We’ll use the Open Ai Gym environment to create Cart-Pole environment and train our agent for Cart-Pole Task. Cart-Pole Task As per Open Ai Gym documentation, here is the Cart Pole Task: A pole is attached by an…
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In the last few blogs, we discussed Reinforcement learning and example, in this blog we discuss another RL example – Tic Tac game. Tic Tac Game – RL Example We all know the Tic tac game, two players take turns playing on a three-by-three board. One player plays Xs and the other Os until one…
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