Left: A man dressed in a loincloth and a woman wearing a flamenco costume talk during the Halloween party in 1981. In addition to iFunny, Discord bot esmBot is a popular tool used to create GIF Captions.Getty Images. Originating from and created on iFunny app, GIF captions saw a significant spread on Twitter and in certain subreddits starting in the second half of 2019. GIF Captions is a genre of memes which consists of a GIF paired with a humorous caption written above.
It’s different from tilting in that the entire camera ascends or descends, rather than just the angle of the camera. A quartet of mummies at Studio 54's annual Halloween party in 1978.1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28A pedestal (AKA Boom up/down or Jib up/down) involves moving the camera upwards or downwards in relation to a subject. Allan Tannenbaum / Getty Images.
Tinder swipe right GIF by Chastity Belt. I Got Curious When You Only Left One Voicemal. Big Brother Canada Drama GIF by Global TV.
Plot3d ( xx , yy , zz , representation = "wireframe" , tube_sides = 5 , line_width =. Sin ( u ) # Points l = mlab. Pi , 100 ) xx , yy , zz = np. Figure ( size = ( 500 , 500 ), bgcolor = ( 1 , 1 , 1 )) u = np.
Screenshot ( antialiased = True ) # return a RGB image animation = mpy. View ( azimuth = 360 * t / duration , distance = 9 ) # camera angle return mlab. Set ( y = y ) # change y-coordinates of the mesh mlab. Sin ( 3 * u ) * ( 0.2 + 0.5 * np.
Write_gif ( "wireframe.gif" , fps = 20 )Vs. Write_videofile ( "wireframe.mp4" , fps = 20 ) animation. Resize ( 0.5 ) # Video generation takes 10 seconds, GIF generation takes 25s animation.
From moviepy.editor import VideoClip import numpy as np from vispy import app , scene from vispy.gloo.util import _screenshot canvas = scene. Be right back brb right wrong funny or die. Share a GIF and browse these related GIF searches. Here is an animation derived from a Mayavi example:The best GIFs for left-or-right. In a dark alley Whitmore (aka Whitty), already upset because of an article about him in the local newspaper, was disturbed by a 'beep bop skeedop' which offered him a battle on his favorite songs.As Mayavi relies on the powerful ITK visualization engine it can also process complex datasets.
Drama Left Right Gif Code Snippets Are
Write_gif ( 'sinc_vispy.gif' , fps = 20 , opt = 'OptimizePlus' )Here are more advanced examples (derived from the Vispy gallery) where C code snippets are embedded in the Python code to fine-tune the 3D shaders:1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Import matplotlib.pyplot as plt import numpy as np from moviepy.video.io.bindings import mplfig_to_npimage import moviepy.editor as mpy # DRAW A FIGURE WITH MATPLOTLIB duration = 2 fig_mpl , ax = plt. Resize ( width = 350 ) animation. Size )) animation = VideoClip ( make_frame , duration = 1 ).
Set_title ( "Elevation in y=0" ) ax. Sin ( xx + d ) # the (changing) z vector ax. Linspace ( - 2 , 2 , 200 ) # the x vector zz = lambda d : np.
Let us watch a SVM classifier getting a better understanding of the map as the number of training point increases.1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32Import numpy as np import matplotlib.pyplot as plt from sklearn import svm # sklearn = scikit-learn from sklearn.datasets import make_moons from moviepy.editor import VideoClip from moviepy.video.io.bindings import mplfig_to_npimage X , Y = make_moons ( 50 , noise = 0.1 , random_state = 2 ) # semi-random data fig , ax = plt. Write_gif ( "sinc_mpl.gif" , fps = 20 )Matplotlib has many beautiful themes and works well with numerical modules like Pandas or Scikit-Learn. VideoClip ( make_frame_mpl , duration = duration ) animation. Pi * t / duration )) # <= Update the curve return mplfig_to_npimage ( fig_mpl ) # RGB image of the figure animation = mpy. Def make_frame_mpl ( t ): line. Plot ( xx , zz ( 0 ), lw = 3 ) # ANIMATE WITH MOVIEPY (UPDATE THE CURVE FOR EACH t).
Set_title ( "SVC classification" , fontsize = 16 ) classifier = svm. Linspace ( - 1 , 2 , 500 )) def make_frame ( t ): ax. Linspace ( - 2 , 3 , 500 ), np. Subplots_adjust ( left = 0 , right = 1 , bottom = 0 ) xx , yy = np.
Linspace ( - 2 , 2 , 20 )) ax. Bone , alpha = 0.8 , vmin =- 2.5 , vmax = 2.5 , levels = np. Contourf ( xx , yy , Z , cmap = plt. Fit ( X , Y , sample_weight = weights ) Z = classifier. Arange ( 50 ))) classifier. Maximum ( 0 , t ** 2 + 10 - np.
France is modelled as a grid (Numpy array) on which all the computations for dispersion and infection are done. Animations with NumpyIf you are working with Numpy arrays ( Numpy is the central numerical library in Python), you don’t need any external plotting library, you can feed the arrays directly to MoviePy.This is well illustrated by this simulation of a zombie outbreak in France (inspired by this blog post by Max Berggren). At the begining it has no real clue, but as more points appear it progressively understands that they are distributed along moon-shaped regions. Write_gif ( "svm.gif" , fps = 15 )Put simply, the background colors tell us where the classifier thinks the black points and white points belong. Bone ) return mplfig_to_npimage ( fig ) animation = VideoClip ( make_frame , duration = 7 ) animation.
Set_position (( "center" , "top" )). TextClip ( title , font = "Purisa-Bold" , fontsize = 15 ). To_mask () def apply_effect ( effect , title , ** kw ): """ Returns a clip with the effect applied and a title""" filtr = lambda im : effect ( im , ** kw ) new_clip = gray. VideoFileClip ( "sinc.gif" ) gray = clip. Import skimage.filter as skf # gaussian blur clip = mpy.
Clips_array (, ]) final_clip. Gaussian_filter , "Blurred" , sigma = 4 ) # Put the clips together on a 2x2 grid, and write to a file. Adjust_log , "Adjusted" ) blurred = apply_effect ( skf. Rescale_intensity , "Rescaled" ) adjusted = apply_effect ( ske. Equalize_hist , "Equalized" ) rescaled = apply_effect ( ske.
Concatenate_videoclips ( clips ) animation. Gaussian_filter , "Blurred" , sigma = 4 ) clips = animation = mpy. Adjust_log , "Adjusted" ) blurred = apply_effect ( skf. Rescale_intensity , "Rescaled" ) adjusted = apply_effect ( ske. Equalize_hist , "Equalized" ) rescaled = apply_effect ( ske.
There is still a lot to do, but it would be nice if authors started relying on it for video and GIF rendering, like Pandas and Scikit-Learn rely on Matplotlib for plotting.For completeness, and because it may better fit your needs, I must mention ImageIO, another Python library with video writing capabilities which focuses on providing a very simple interface to read or write any kind of image, video or volumetric data. Thanks to the many users who have tested it in very different contexts, MoviePy seems to have become stable (or people stopped reporting bugs), and can be adapted to many situations. Any other library could be animated with MoviePy, as long as its output can be converted to a Numpy array.Some libraries have their own animation modules, but these are usually a pain to fix and maintain. The third panel shows that the population size grows exponentially in time.I hope to have given you enough recipes to impress your colleagues at your next presentation. For our last example we estimate the size of a growing bacterial population by thresholding the video frames and counting the white pixels.
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