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Is there a way to take a bunch of images and turn them into an mp4 file in java?

I am currentrly working on a Way to visualize Fractals in Java. The mathematics behind it work perfectly fine and I am very happy with how the Pics turn out. Now i want to take these Images and turn them into a Video. I've written a Java Program that produces any number of Pictures and saves them (alphabetically) in a new directory. Now I need a way for Java to convert these Images into a Video.
I know there are solutions such as ffmpeg, however I need this process to be repeatable, so I don't think a Command Line Application would be the best Option.
Is there any Way to implement such a function into Java directly ?

If you're willing to use a third party library and the platform is supported (Windows or Linux, 64bit). You can use Pilecv4j (Full disclosure, I'm the main committer).
There's a test checked in that does exactly this. You can find it here: TestSplitIntoFiles.java
Here is the pertinent function that does this with the minor difference that it's not reading the image file names from the contents on the disk:
private static void encodeFiles(final File imageDir, final long numFrames, final File outputVideo) throws IOException {
try(final CvMat firstFrame = ImageFile.readMatFromFile(new File(imageDir, "image-0.jpg").getAbsolutePath());
final EncodingContext ectx = Ffmpeg2.createEncoder()
.outputStream(outputVideo.getAbsolutePath())
.openVideoEncoder("libx264", "vidEncoder")
.addCodecOptions("preset", "slow")
.addCodecOptions("crf", "40")
.enable(firstFrame, false)
;) {
final VideoEncoder ve = ectx.getVideoEncoder("vidEncoder");
ectx.ready();
LongStream.range(0, numFrames)
.mapToObj(fn -> new File(imageDir, "image-" + fn + ".jpg").getAbsolutePath())
.forEach(frameFile -> {
try(CvMat mat = uncheck(() -> ImageFile.readMatFromFile(frameFile));) {
ve.encode(mat, false);
}
});
}
}
If you decide to give it a try, let me know if you run into any issues. You can use the Issues on GitHub. I've been using it professionally for a while.
Also, see the answer to this question: Read a mp4 and write to anther mp4 creates bigger size

Does JCODEC Support MPEG-TS or MPEG-PS

I am trying to be able to pick out frames (video and metadata) from MPEG, MPEG-TS and MPEG-PS files and live streams (network / UDP / RTP streams). I was looking into using JCODEC to do this and I started off by trying to use the FrameGrab / FrameGrab8Bit classes, and ran into an error that those formats are "temporarily unsupported". I looked into going back some commits to see if I could just use older code, but it looks like both of those files have had those formats "temporarily unsupported" since 2013 / 2015, respectively.
I then tried to plug things back into the FrameGrab8Bit class by putting in the below code...
public static FrameGrab8Bit createFrameGrab8Bit(SeekableByteChannel in) throws IOException, JCodecException {
...
SeekableDemuxerTrack videoTrack = null;
...
case MPEG_PS:
MPSDemuxer psd = new MPSDemuxer(in);
List tracks = psd.getVideoTracks();
videoTrack = (SeekableDemuxerTrack)tracks.get(0);
break;
case MPEG_TS:
in.setPosition(0);
MTSDemuxer tsd = new MTSDemuxer(in);
ReadableByteChannel program = tsd.getProgram(481);
MPSDemuxer ptsd = new MPSDemuxer(program);
List<MPEGDemuxerTrack> tstracks = ptsd.getVideoTracks();
MPEGDemuxerTrack muxtrack = tstracks.get(0);
videoTrack = (SeekableDemuxerTrack)tstracks.get(0);
break;
...
but I ran into a packet header assertion failure in the MTSDemuxer.java class in the parsePacket function:
public static MTSPacket parsePacket(ByteBuffer buffer) {
int marker = buffer.get() & 0xff;
int marker = by & 0xff;
Assert.assertEquals(0x47, marker);
...
I found that when I reset the position of the seekable byte channel (i.e.: in.setPosition(0)) the code makes it past the assert, but then fails at videoTrack = (SeekableDemuxerTrack)tstracks.get(0) (tstracks.get(0) cannot be converted to a SeekableDemuxerTrack)
Am I waisting my time? Are these formats supported somewhere in the library and I am just not able to find them?
Also, after going around in the code and making quick test applications, it seems like all you get out of the demuxers are video frames. Is there no way to get the metadata frames associated with the video frames?
For reference, I am using the test files from: http://samples.ffmpeg.org/MPEG2/mpegts-klv/

In case anyone in the future also has this question. I got a response from a developer on the project's GitHub page to this question. Response:
Yeah, MPEG TS is not supported to the extent MP4 is. You can't really seek in TS streams (unless you index the entire stream before hand).
I also asked about how to implement the feature. I thought that it could be done by reworking the MTSDemuxer class to be built off of the SeekableDemuxerTrack so that things would be compatible with the FrameGrab8Bit class, and got the following response:
So it doesn't look like there's much sense to implement TS demuxer on top of SeekableDemuxerTrack. We haven't given much attention to TS demuxer actually, so any input is very welcome.
I think this (building the MTSDemuxer class off of the SeekableDemuxerTrack interface) would work for files (since you have everything already there). But without fully fleshing out that thought, I could not say for sure (it definitely makes sense that this solution would not work for a live MPEG-TS / PS connection).

How to create a tensorflow serving client for the 'wide and deep' model?

I've created a model based on the 'wide and deep' example (https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/learn/wide_n_deep_tutorial.py).
I've exported the model as follows:
m = build_estimator(model_dir)
m.fit(input_fn=lambda: input_fn(df_train, True), steps=FLAGS.train_steps)
results = m.evaluate(input_fn=lambda: input_fn(df_test, True), steps=1)
print('Model statistics:')
for key in sorted(results):
print("%s: %s" % (key, results[key]))
print('Done training!!!')
# Export model
export_path = sys.argv[-1]
print('Exporting trained model to %s' % export_path)
m.export(
export_path,
input_fn=serving_input_fn,
use_deprecated_input_fn=False,
input_feature_key=INPUT_FEATURE_KEY
My question is, how do I create a client to make predictions from this exported model? Also, have I exported the model correctly?
Ultimately I need to be able do this in Java too. I suspect I can do this by creating Java classes from proto files using gRPC.
Documentation is very sketchy, hence why I am asking on here.
Many thanks!

I wrote a simple tutorial Exporting and Serving a TensorFlow Wide & Deep Model.
TL;DR
To export an estimator there are four steps:
Define features for export as a list of all features used during estimator initialization.
Create a feature config using create_feature_spec_for_parsing.
Build a serving_input_fn suitable for use in serving using input_fn_utils.build_parsing_serving_input_fn.
Export the model using export_savedmodel().
To run a client script properly you need to do three following steps:
Create and place your script somewhere in the /serving/ folder, e.g. /serving/tensorflow_serving/example/
Create or modify corresponding BUILD file by adding a py_binary.
Build and run a model server, e.g. tensorflow_model_server.
Create, build and run a client that sends a tf.Example to our tensorflow_model_server for the inference.
For more details look at the tutorial itself.

Just spent a solid week figuring this out. First off, m.export is going to deprecated in a couple weeks, so instead of that block, use: m.export_savedmodel(export_path, input_fn=serving_input_fn).
Which means you then have to define serving_input_fn(), which of course is supposed to have a different signature than the input_fn() defined in the wide and deep tutorial. Namely, moving forward, I guess it's recommended that input_fn()-type things are supposed to return an InputFnOps object, defined here.
Here's how I figured out how to make that work:
from tensorflow.contrib.learn.python.learn.utils import input_fn_utils
from tensorflow.python.ops import array_ops
from tensorflow.python.framework import dtypes
def serving_input_fn():
features, labels = input_fn()
features["examples"] = tf.placeholder(tf.string)
serialized_tf_example = array_ops.placeholder(dtype=dtypes.string,
shape=[None],
name='input_example_tensor')
inputs = {'examples': serialized_tf_example}
labels = None # these are not known in serving!
return input_fn_utils.InputFnOps(features, labels, inputs)
This is probably not 100% idiomatic, but I'm pretty sure it works. For now.

OpenCV Constants.CaptureProperty

Hi I use OpenCV Java and have some problem.
I open video file and try get property like FPS.
And others:
CV_CAP_PROP_POS_MSEC
CV_CAP_PROP_FRAME_COUNT
So first I opened video like this:
VideoCapture vC = new VideoCapture(url2);
and next i have a problem with function
vC.get(int i)
in OpenCV C++ its look like
vC.get(CV_CAP_PROP_FPS);
In Java where I find this constants?In HighGui I didnt find them. Only what I find is another libary to OpenCV where are this constants http://siggiorn.com/wp-content/uploads/libraries/opencv-java/docs/sj/opencv/Constants.CaptureProperty.html. But where I find them in OpenCV Java. Anyway how I have to use vC.get() function? Maybe some working example?

There is a bug report about this issue.
Until it is fixed, I suggest that you find these constants in the C++ source code, and define them yourself.
Edit:
I was just curious myself. You find them in the file modules/highgui/include/opencv2/highgui.hpp They are:
CAP_PROP_POS_MSEC =0,
CAP_PROP_POS_FRAMES =1,
CAP_PROP_POS_AVI_RATIO =2,
CAP_PROP_FRAME_WIDTH =3,
CAP_PROP_FRAME_HEIGHT =4,
CAP_PROP_FPS =5,
CAP_PROP_FOURCC =6,
CAP_PROP_FRAME_COUNT =7,
CAP_PROP_FORMAT =8,
CAP_PROP_MODE =9,
CAP_PROP_BRIGHTNESS =10,
CAP_PROP_CONTRAST =11,
CAP_PROP_SATURATION =12,
CAP_PROP_HUE =13,
CAP_PROP_GAIN =14,
CAP_PROP_EXPOSURE =15,
CAP_PROP_CONVERT_RGB =16,
CAP_PROP_WHITE_BALANCE_BLUE_U =17,
CAP_PROP_RECTIFICATION =18,
CAP_PROP_MONOCROME =19,
CAP_PROP_SHARPNESS =20,
CAP_PROP_AUTO_EXPOSURE =21, // DC1394: exposure control done by camera, user can adjust refernce level using this feature
CAP_PROP_GAMMA =22,
CAP_PROP_TEMPERATURE =23,
CAP_PROP_TRIGGER =24,
CAP_PROP_TRIGGER_DELAY =25,
CAP_PROP_WHITE_BALANCE_RED_V =26,
CAP_PROP_ZOOM =27,
CAP_PROP_FOCUS =28,
CAP_PROP_GUID =29,
CAP_PROP_ISO_SPEED =30,
CAP_PROP_BACKLIGHT =32,
CAP_PROP_PAN =33,
CAP_PROP_TILT =34,
CAP_PROP_ROLL =35,
CAP_PROP_IRIS =36,
CAP_PROP_SETTINGS =37

use class import org.opencv.videoio.Videoio;
vc.open(FD.class.getResource("1.avi").getPath());
double totalFrameNumber = vc.get(Videoio.CAP_PROP_FRAME_COUNT);
System.out.println("\n"+totalFrameNumber);

It seems the bug is solved. Now you should be able to use it as:
VideoCapture vC = new VideoCapture(...);
nbFrames = vC.get(Videoio.CAP_PROP_FRAME_COUNT);

Capturing a single image from my webcam in Java or Python

I want to capture a single image from my webcam and save it to disk. I want to do this in Java or Python (preferably Java). I want something that will work on both 64-bit Win7 and 32-bit Linux.
EDIT: I use Python 3.x, not 2.x
Because everywhere else I see this question asked people manage to get confused, I'm going to state a few things explicitly:
I do not want to use Processing
I do not want to use any language other than those stated above
I do want to display this image on my screen in any way, shape or form
I do not want to display a live video feed from my webcam on my screen, or save such a feed to my hard drive
The Java Media Framework is far too out of date. Do not suggest it.
I would rather not use JavaCV, but if I absolutely must, I want to know exactly which files from the OpenCV library I need, and how I can use these files without including the entire library (and preferably without sticking these files in any sort of PATH. Everything should be included in the one directory)
I can use Eclipse on the 64-bit Win7 computer if need be, but I also have to be able to compile and use it on 32-bit Linux as well
If you think I might or might not know something related to this subject in any way shape or form, please assume I do not know it, and tell me
EDIT2: I was able to get Froyo's pygame example working on Linux using Python 2.7 and pygame 1.9.1. the pygame.camera.camera_list() call didn't work, but it was unnecessary for the rest of the example. However, I had to call cam.set_controls() (for which you can find the documentation here http://www.pygame.org/docs/ref/camera.html) to up the brightness so I could actually see anything in the image I captured.
Also, I need to call the cam.get_image() and pygame.image.save() methods three times before the image I supposedly took on the first pair of calls actually gets saved. They appeared to be stuck in a weird buffer. Basically, instead of calling cam.get_image() once, I had to call it three times every single time I wanted to capture an image. Then and only then did I call pygame.image.save().
Unfortunately, as stated below, pygame.camera is only supported on Linux. I still don't have a solution for Windows.

#thebjorn has given a good answer. But if you want more options, you can try OpenCV, SimpleCV.
using SimpleCV (not supported in python3.x):
from SimpleCV import Image, Camera
cam = Camera()
img = cam.getImage()
img.save("filename.jpg")
using OpenCV:
from cv2 import *
# initialize the camera
cam = VideoCapture(0) # 0 -> index of camera
s, img = cam.read()
if s: # frame captured without any errors
namedWindow("cam-test",CV_WINDOW_AUTOSIZE)
imshow("cam-test",img)
waitKey(0)
destroyWindow("cam-test")
imwrite("filename.jpg",img) #save image
using pygame:
import pygame
import pygame.camera
pygame.camera.init()
pygame.camera.list_cameras() #Camera detected or not
cam = pygame.camera.Camera("/dev/video0",(640,480))
cam.start()
img = cam.get_image()
pygame.image.save(img,"filename.jpg")
Install OpenCV:
install python-opencv bindings, numpy
Install SimpleCV:
install python-opencv, pygame, numpy, scipy, simplecv
get latest version of SimpleCV
Install pygame:
install pygame

On windows it is easy to interact with your webcam with pygame:
from VideoCapture import Device
cam = Device()
cam.saveSnapshot('image.jpg')
I haven't tried using pygame on linux (all my linux boxen are servers without X), but this link might be helpful http://www.jperla.com/blog/post/capturing-frames-from-a-webcam-on-linux

import cv2
camera = cv2.VideoCapture(0)
while True:
return_value,image = camera.read()
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
cv2.imshow('image',gray)
if cv2.waitKey(1)& 0xFF == ord('s'):
cv2.imwrite('test.jpg',image)
break
camera.release()
cv2.destroyAllWindows()

Some time ago I wrote simple Webcam Capture API which can be used for that. The project is available on Github.
Example code:
Webcam webcam = Webcam.getDefault();
webcam.open();
try {
ImageIO.write(webcam.getImage(), "PNG", new File("test.png"));
} catch (IOException e) {
e.printStackTrace();
} finally {
webcam.close();
}

I wrote a tool to capture images from a webcam entirely in Python, based on DirectShow. You can find it here: https://github.com/andreaschiavinato/python_grabber.
You can use the whole application or just the class FilterGraph in dshow_graph.py in the following way:
from pygrabber.dshow_graph import FilterGraph
import numpy as np
from matplotlib.image import imsave
graph = FilterGraph()
print(graph.get_input_devices())
device_index = input("Enter device number: ")
graph.add_input_device(int(device_index))
graph.display_format_dialog()
filename = r"c:\temp\imm.png"
# np.flip(image, axis=2) required to convert image from BGR to RGB
graph.add_sample_grabber(lambda image : imsave(filename, np.flip(image, axis=2)))
graph.add_null_render()
graph.prepare()
graph.run()
x = input("Press key to grab photo")
graph.grab_frame()
x = input(f"File {filename} saved. Press key to end")
graph.stop()

It can be done by using ecapture
First, run
pip install ecapture
Then in a new python script
type:
from ecapture import ecapture as ec
ec.capture(0,"test","img.jpg")
More information from thislink

I am able to achieve it, this way in Python (Windows 10):
Please install PyAutoGUI
import pyautogui as pg #For taking screenshot
import time # For necessary delay
import subprocess
# Launch Windows OS Camera
subprocess.run('start microsoft.windows.camera:', shell=True)
time.sleep(2) # Required !
img=pg.screenshot() # Take screenshot using PyAutoGUI's function
time.sleep(2) # Required !
img.save(r"C:\Users\mrmay\OneDrive\Desktop\Selfie.PNG") # Save image screenshot at desired location on your computer
#Close the camera
subprocess.run('Taskkill /IM WindowsCamera.exe /F', shell=True)