Cv2 Save Numpy Array As Image

py ith_Python_Second_Edition_Code/Chapter 3_Code/contours. imwrite() Wait for keyboard button press using cv2. combine_slices (slice_datasets, rescale=None) ¶ Given a list of pydicom datasets for an image series, stitch them together into a three-dimensional numpy array. There are functions for rotating or flipping images (= ndarray) in OpenCV and NumPy, either of which can be used. isClosed - Flag indicating whether the drawn polylines are closed or not. I converted the image to a numpy array and performed filtering operations. Matching Features with ORB using OpenCV (Python code) the first funtion returns the image we are trying to match to our video, the parameter is the name of the. A Haar Cascade is an object detection method used to locate an object of interest in images. How can I display the array with cv2. Difference between Matrix Arithmetic in OpenCV and Numpy Hi, This is a small post to show you an important difference in arithmetic operations in OpenCV and Numpy. Here, image files are read as NumPy array ndarray using Pillow. destroyAllWindows() On running above code, a screenshot of the window will look like this, Write an image. The ability to add lines, circles and geometric shapes over an image is an operation that will prove very useful. save(file, arr, allow_pickle=True, fix_imports=True) Parameters: file :: File or filename to which the data is saved. Replace rows an columns by zeros in a numpy array. I have a matrix in the type of a Numpy array. # The conversion from PIL to OpenCV is done with the handy NumPy method "numpy. Your captured image should be a numpy array with a row for each of the three color channels; you can just use the first channel as a greyscale image and save yourself some data processing. In this tutorial, you will use a pre-trained Haar Cascade from OpenCV to detect and extract faces from an image. imread('messi. It is not part of a standard Python installation, it is downloaded and installed separately if needed. NumPy is a package for scientific computing with Python. imread and opencv cv2. Array data to be. COLOR_RGB2BGR) cv2. We use Hough Transform technique to get the center of a car, by voting in matrix or array with the size of the (x=image/10, y=image/10), we make one vote with calculate center of the car and. export data and labels in cvs file. On the last line of that script, image is a numpy array with shape (rows, cols, color-plane) with the color planes in BGR order - which is precisely how OpenCV represents image data. Building blocks. jpg image file and 1 to read image as full color, if 0 to read image as grayscale, if -1 will be opened as is. imshow('image',img). 'image' is a reference to an element of a list of numpy arrays. imread(), so it doesn't matter which OpenCV or Pillow is used, but be aware that the color order is different. It is the default flag. arr array_like. uint8(myarray* 255)) python - How to convert Numpy array to PIL image applying matplotlib colormap - Stack Overflow. Create an Object Detector. Image,OpenCV,Numpy, 二进制流, base64编码 】之间图像格式相互转换 - imgmatformatconvert. gamma is static weight that will be added to all the pixels of the image. IMREAD_UNCHANGED : Loads image as such including alpha channel; Returns numpy array, containing the pixel values. empty((2,2)). An alpha layer may be included, specified as the last colour band of an MxNx4 array. In this post, I describe how to convert numpy image or PIL Image object to binary data without saving the underlying image. Camera capture (opencv02. # Load library import cv2 import numpy as np from matplotlib import pyplot as plt Load Image As Greyscale # Load image as grayscale image = cv2. imwrite() to save an image. This variable contains all of the spatial metadata for naip data. imwrite() Wait for keyboard button press using cv2. Arrays are powerful structures, as we saw briefly in the previous tutorial. imread("red_panda. Arrays and working with Images. Jpeg: Colorspace Transform, Subsampling, DCT and Quantisation¶ In this document the first 4 steps of the JPEG encoding chain are demonstrated. The remaining steps, i. waitKey() Exit window and destroy all windows using cv2. These are the top rated real world Python examples of numpy. The NumPy array as universal data structure in OpenCV for images, extracted feature points, filter kernels and many more vastly simplifies the. image as mpimg img = mpimg. How to convert between NumPy array and PIL Image. detectMultiScale(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize]]]]]) -> objects @brief Detects objects of different sizes in the input image. jpg") The image is now treated as a matrix with rows and columns values stored in img. For colored images, each pixel is represented as an array containing Red, Green and Blue channels. Let's start off with the imports. This code to call numpy and opencv packages. The installation instructions for OpenCV should guide you through configuring the project for yourself. multiarray failed to import"最主要的原因是opencv3版本依赖出现问题,太新的numpy版本会导致cv2引用出错,所以出现此类问题,不防降低numpy版本试试!. imwrite("filename. I finally found a way of piping raw numpy buffers as frames to mencoder. This chapter describes how to use scikit-image on various image processing tasks, and insists on the link with other scientific Python modules such as NumPy and SciPy. There are various ways, but one possibility is to create a 2D numpy array with your random data. detectMultiScale(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize]]]]]) -> objects @brief Detects objects of different sizes in the input image. imdecode Convert URL to image with Python and OpenCV. zeros to create a 250 x 250 x 3 float64 tensor to hold the result 3. def image_batch_generator(df,images_path, batch_size): ''' A generator that takes a dataframe (for image names) and with a given image path goes to conver images to numpy array over batch (chunk by chunk). py from CS 6475 at Georgia Institute Of Technology. imwrite(path, im. Second argument is a flag which specifies the way image should be read. Questions: I'm trying to use matplotlib to read in an RGB image and convert it to grayscale. Parameters: file: file or str. If file is a string or Path, a. imread('0000001. How to convert a python numpy array to an RGB image with Opencv 2. Prerequisite : Basics of OpenCV In this article we'll try to open an image by using OpenCV (Open Source Computer Vision). imshow() Save the output in an image file using cv2. 2 NaN 2 NaN NaN 0. "Drawing Image using Numpy and Opencv" is published by Manivannan Murugavel. imread() to read an image. Numpy array of rank 4 or a tuple. Let's detect the green color from an image: Import the modules cv2 for images and NumPy for image arrays: import cv2 import numpy as np Read the image and convert it into HSV using cvtColor():. array(imPaths,dtype="unicode") np. imwrite() to save an image. img_array = [] the memory required for the image array can be. What is the difference between convolutional layer and linear layer? What kind of intuition is in behind of using convolutional layer in deep neural network?This hands on shows some effects by convolutional layer to provide some intution about. Read the elements of a using this index order, and place the elements into the reshaped array using this index order. VideoWriter. write() Wait for keyboard button press using cv2. jpg',1) This code to show image on variable img. 4? Ask Question and I would like to display and/or save it as a BGR image using OpenCV (cv2). I'm trying to read an image using cv2. Arbitrary data-types can be defined. Now, if these square tiles are too big, it's then hard to make smooth edges and curves. The fromstring/tostring approach may look a bit crude, but experiments (by others) indicate that the result is about as fast as it can get, on most modern platforms. py) Reference: PiCamera API Type (or copy and paste) the following code and save it as opencv02. if you want a copy, use. This section will present several examples of using NumPy array manipulation to access data and subarrays, and to split, reshape, and join the arrays. If you convert the image into gray scale and use the received image in dlib (face_recognition) then library complains with RuntimeError: Unsupported image type, must be 8bit gray or RGB image. (from Travis Oliphant). MATLAB/Octave Python Description; zeros(3,5) zeros((3,5),Float) 0 filled array: zeros((3,5)) 0 filled array of integers: ones(3,5) ones((3,5),Float) 1 filled array: ones(3,5)*9: Any number filled array: eye(3) identity(3) Identity matrix: diag([4 5 6]) diag((4,5,6)) Diagonal: magic(3) Magic squares; Lo Shu: a = empty((3,3)) Empty array. jpg image file and 1 to read image as full color, if 0 to read image as grayscale, if -1 will be opened as is. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. We use cookies for various purposes including analytics. Numpy / OpenCV image BGR to RGB 1 October, 2019. in opencv we can read. imread() Display Image using cv2. write() Wait for keyboard button press using cv2. Python opencv-Writing numpy object data to image file. Please suggest currently I have a matrix in the type of a Numpy array, so how would I write it to disk as an image, it can be of any format png, jpeg, bmp, just remember one important constraint that here PIL is not present. jpg") The image is now treated as a matrix with rows and columns values stored in img. imshow(): M x N x 3 image, where last dimension is RGB. Questions: I’m trying to use matplotlib to read in an RGB image and convert it to grayscale. Pick a face with at least 100 images. But a lot of times, we would like to read an image from a URL and process it in OpenCV. imwrite() to save an image. array" which converts the PIL image into a NumPy array. An important point to make is that you can always simply save your images as PNG files, and then use any software that you like to create an animated GIF. Signal Processing with NumPy II - Image Fourier Transform : FFT & DFT Inverse Fourier Transform of an Image with low pass filter: cv2. imshow('Display', image) cv2. Python uint16 - 30 examples found. waitKey(0) cv2. In particular, the submodule scipy. image = cv2. Save an array to a binary file in NumPy. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. If file is a file-object, then the filename is unchanged. destroyAllWindows() For color image, opencv uses a three dimensional array to store intensity of Blue, Red, and Green. What gives?. # Load library import cv2 import numpy as np from matplotlib import pyplot as plt Load Image As Greyscale # Load image as grayscale image = cv2. In the image below, you’ll see three buttons labeled 1-3 that will be important for you to get a grasp of the save button (1), the add cell button (2), and the run cell button (3). Camera capture (opencv02. Rotate image with OpenCV: cv2. This variable contains all of the spatial metadata for naip data. Read each image with skimage. For individual pixel access, the Numpy array methods, array. 4? Ask Question and I would like to display and/or save it as a BGR image using OpenCV (cv2). In this tutorial, we are going to work with an image, in order to visualise changes to an array. So whatever operations you can do in Numpy, you can combine it with OpenCV, which increases number of weapons in your arsenal. imread(“input. image as mpimg img = mpimg. 4? Ask Question and I would like to display and/or save it as a BGR image using OpenCV (cv2). VideoWriter. October 1998 | Fredrik Lundh. In the image below, you’ll see three buttons labeled 1-3 that will be important for you to get a grasp of the save button (1), the add cell button (2), and the run cell button (3).  While we tend to. Now, I have some code that will show us what the difference is. We will create numpy array. idft() Image Histogram Video Capture and Switching colorspaces - RGB / HSV Adaptive Thresholding - Otsu's clustering-based image thresholding Edge Detection - Sobel and Laplacian Kernels Canny Edge Detection. Using the shape and reshape tools available in the NumPy module, configure a list according to the guidelines. Array data to be. So, Our GoalIn this session, 1. Let's start off with the imports. Jadi operasi apa pun dapat Anda lakukan di Numpy, Anda dapat menggabungkan itu dengan OpenCV, yang meningkatkan jumlah senjata di gudang senjata Anda. Display the rotated image: cv2. Home; camera and return the data as an OpenCV image (which is a numpy array). OpenCV Resources Reading and Writing Images Write an Image Use the function cv2. ncontours – Number of curves. If axis is None, out is a flattened array. We use cookies for various purposes including analytics.  While we tend to. jpg") The image is now treated as a matrix with rows and columns values stored in img. How can I save it as a single band image?. Create feature extraction and key point detector objects. Convert python numpy array to double. Here, the following contents will be described. Technically, the OpenCV bindings for Python store an image in a NumPy array. img_array = [] the memory required for the image array can be. copy() method on the array!. NB : This answer is a short compilation of comments above. I'm working on MODIS NDVI composite data (single band). Matplotlib pyplot. imshow(): M x N x 3 image, where last dimension is RGB. npy extension will be appended to the file name if it does not already have one. NUMPY The key to NumPy is the ndarray object, an n-dimensional array of homogeneous data types, with many operations being performed in compiled code for performance. It provides high-level performance on multidimensional array objects. npy extension will be appended to the filename if it does not already have one. With Python using NumPy and SciPy you can read, extract information, modify, display, create and save image data. Use the "Preview Post" button to make sure the code is presented as you expect before hitting the "Post Reply/Thread" button. imshow("Rotated Image", rotated_img) cv2. in opencv we can read. Source code is uploaded on github. Here are the examples of the python api cv2. The following are code examples for showing how to use cv2. SetWindowPos(). TensorFlow operations automatically convert NumPy ndarrays to Tensors. Following is what I have chosen to define the range of green color in. @param image Matrix of the type CV_8U containing an image where objects are detected. destroyAllWindows() On running above code, a screenshot of the window will look like this, Write an image. Basic Image Handling and Processing This chapter is an introduction to handling and processing images. def opencv_image_as_array (im): """Interface image from OpenCV's native format to a numpy array. Signal Processing with NumPy II - Image Fourier Transform : FFT & DFT Inverse Fourier Transform of an Image with low pass filter: cv2. OpenCV プログラム例# 頑張って各行に画像を入れる (imgvec=numpy. To get started, we need to import the cv2 module, which will make available the functionalities needed to read the original image and to convert it to gray scale. imwrite("in_memory_to_disk. If you are working in python environment Spyder, then it cannot get more easier than to just right click the array in variable explorer, and then choose Show Image option. array(PILImage), cv2. image as mpimg img = mpimg. Sharing image data between ZED SDK and OpenCV Python. Let's start off with the imports. I have a matrix in the type of a Numpy array. Let's start by loading the next image using OpenCV: 1 import tkinter 2 import cv2 3 import PIL. py) Reference: PiCamera API Type (or copy and paste) the following code and save it as opencv02. Finally, we calculate the pixel-wise mean of the train set and save it in an array with the shape of (1, image_height, image_width, image_depth). And with __no__ lag please. OpenCV is an open source Computer Vision and Image Processing Library made up of over 2500 algorithms. imdecode Convert URL to image with Python and OpenCV. write() Wait for keyboard button press using cv2. imread() Display Image using cv2. Let's start by loading the next image using OpenCV: 1 import tkinter 2 import cv2 3 import PIL. jpg") The image is now treated as a matrix with rows and columns values stored in img. com NumPy DataCamp Learn Python for Data Science Interactively The NumPy library is the core library for scientific computing in Python. This article shows how a CNN is implemented just using NumPy. We're using cv2, numpy and a little bit of matplotlib (mostly as a convenient way of displaying images). 2 NaN 2 NaN NaN 0. Following is what I have chosen to define the range of green color in. Original. 4 ! A computer vision library with lots of algorithms and I/O features ! OpenCV Python treats images as NumPy arrays. Then in function crop_rect(), we calculate a rotation matrix and rotate the original image around the rectangle center to straighten the rotated rectangle. Takes an image and a full_object_detections object that reference faces in that image and returns the faces as a list of Numpy arrays representing the image. This variable contains all of the spatial metadata for naip data. Computer store images as a mosaic of tiny squares. Hey guys, been reading OpenCV for python and thought of posting a tutorial on Programming a Grayscale Image Convertor. imshow() Save the output in an image file using cv2. Second argument is a flag which specifies the way image should be read. This returns the image data in to form of a 3D numpy array, similar to how matplotlib works but. imdecode taken from open source projects. We can crop the photo so we are only focused on the painting itself. Tags: image , opencv , python. VideoWriter() import cv2 import numpy as np import glob. matlib >>> matrix = np. npy extension will be appended to the file name if it does not already have one. py) Reference: PiCamera API Type (or copy and paste) the following code and save it as opencv02. fromarrayでできる。与えるのはuint8である必要があるらしい。 from PIL import Image im = Image. In other words, you can just pass that array straight to OpenCV functions:. No, they are to slow, you need to use Numpy. This section addresses basic image manipulation and processing using the core scientific modules NumPy and SciPy. 4 ! A computer vision library with lots of algorithms and I/O features ! OpenCV Python treats images as NumPy arrays. array import time #from fractions import Fraction class gopigo_control: # Init various camera parameter. png') In the code below we will: Create a 200 by 100 pixel array; Use slice notation to fill left half of the array with orange; Use slice notation to fill right half of the array. In this tutorial we will learn that how to do image segmentation using OpenCV. Skin Detection Using OpenCV Python. The fromstring/tostring approach may look a bit crude, but experiments (by others) indicate that the result is about as fast as it can get, on most modern platforms. Reading an image from a file is fairly straightforward in OpenCV-Python. Your captured image should be a numpy array with a row for each of the three color channels; you can just use the first channel as a greyscale image and save yourself some data processing. save(args["annotations"],annotations) np. So whatever operations you can do in Numpy, you can combine it with OpenCV, which increases number of weapons in your arsenal. It is the default flag. If you are working in python environment Spyder, then it cannot get more easier than to just right click the array in variable explorer, and then choose Show Image option. imshow('Display', image) cv2. share | improve this answer. Tensors are explicitly converted to NumPy ndarrays using their. Let's start by loading the next image using OpenCV: 1 import tkinter 2 import cv2 3 import PIL. OpenCV プログラム例# 頑張って各行に画像を入れる (imgvec=numpy. jpg') # convert RGB to BGR. For more details, please refer to the comments below question. They are extracted from open source Python projects. imread() Initialize the video writer using cv2. This will return an image as a numpy ndarray. An important point to make is that you can always simply save your images as PNG files, and then use any software that you like to create an animated GIF. Load Image using cv2. Iterating over list of tuples. the outer one is the list of contours, the inner ones are the points of a single. Original. IMREAD_COLOR : Loads a color image. All of these values have the same data type (in this case, they are integers). imwrite(path, im. It is the default flag. The following are code examples for showing how to use cv2. zeros((10,10))) useful if you need to do more processing other than saving. Line 8 is where the actual clustering happens. Read each image with skimage. dicom_numpy. The ability to add lines, circles and geometric shapes over an image is an operation that will prove very useful. In this tutorial, we are going to see some more image manipulations using Python OpenCV. So, Our GoalIn this session, 1. imwrite("filename. The Keras API also provides the save_img() function to save an image to file. Call numpy. imwrite() Wait for keyboard button press using cv2. imshow? cv2. Introduction Sometimes, we want an in-momery jpg or png image that is represented as binary data. They are extracted from open source Python projects. You can easily view a HD movie with VLC and see it too in the OpenCV window. IMREAD_COLOR : Loads a color image. itemset() are considered better, however they always return a scalar. Use the function cv2. / OpenCV Object Tracking by Colour Detection in Python OpenCV Object Tracking by Colour Detection in Python Hi everyone, we have already seen lots of advanced detection and recognition techniques, but sometime its just better with old school colour detection techniques for multiple object tracking. This returns the image data in to form of a 3D numpy array, similar to how matplotlib works but. Images as Arrays. screenshot() image = cv2. OpenCV is an open source Computer Vision and Image Processing Library made up of over 2500 algorithms. If you are working in python environment Spyder, then it cannot get more easier than to just right click the array in variable explorer, and then choose Show Image option. Please modify the code below to show the image in Fig 1. Views share the underlying storage of the original array. destroyAllWindows() Example Code:. NumPy Array Object Exercises, Practice and Solution: Write a NumPy program to append values to the end of an array. It takes a string argument. item() separately for all. MATLAB commands in numerical Python (NumPy) 3 Vidar Bronken Gundersen /mathesaurus. imread('0000001. Using OpenCV and Python on the Raspberry Pi for simple object detection Posted on 2015-04-06 by admin I wrote some time ago about the robot which task it is to find a blue ball and move to it. The NumPy array as universal data structure in OpenCV for images, extracted feature points, filter kernels and many more vastly simplifies the. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. It is not part of a standard Python installation, it is downloaded and installed separately if needed. In general cases, we read image using cv2. The following are code examples for showing how to use cv2. img_array = [] the memory required for the image array can be. array import time #from fractions import Fraction class gopigo_control: # Init various camera parameter. empty() This function returns a new matrix filled with the random data. minAreaRect() method. IMREAD_UNCHANGED : Loads image as such including alpha channel; Returns numpy array, containing the pixel values. imread(), so it doesn't matter which OpenCV or Pillow is used, but be aware that the color order is different. Here, the following contents will be described. This post is to explain how fast array manipulation can be done in Numpy. contourごとにcv2. imread, but the raw data differs. save(file, arr, allow_pickle=True, fix_imports=True) Parameters: file :: File or filename to which the data is saved. imread(“input. (from Travis Oliphant). We can see that whichever bumbling fool took that photo of the painting also captured a lot of the wall. imshow('image',img). >>> example for single band, from numpy 'C' array >>> # (the case which L values are represented by 8bit integers) >>> from __future__ import print_function. 'image' is a reference to an element of a list of numpy arrays. imshow('image',img) #key binding function cv2. VideoWriter() Save the frames to a video file using cv2. The torch Tensor and numpy array will share their underlying memory locations, and changing one will change the other. “Create Numpy array of images” is published by muskulpesent. A simple program using all functions: import numpy as np import cv2 img = cv2. SetWindowPos(). They are extracted from open source Python projects. where 14965 is the number of images. Face Detection+recognition: This is a simple example of running face detection and recognition with OpenCV from a camera. This post is to explain how fast array manipulation can be done in Numpy. They just read in the image import matplotlib. png') In the code below we will: Create a 200 by 100 pixel array; Use slice notation to fill left half of the array with orange; Use slice notation to fill right half of the array. Rotate image with OpenCV: cv2. imshow('image',img). IMREAD_COLOR. Python Image Processing With OpenCV There are many image processing packages for Python. release() Exit window and destroy all windows using cv2. If you want, you can do something like to print the whole array. It is not part of a standard Python installation, it is downloaded and installed separately if needed. destroyAllWindows() On running above code, a screenshot of the window will look like this, Write an image. File or filename to which the data is saved. To save an image to the local file system, use cv2. If axis is None, out is a flattened array. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: