معرفی شرکت ها
ProcessedPiRecorder-0.3.1
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
Multiprocessed picamera class for simpler and faster computer vision
| ویژگی | مقدار |
|---|---|
| سیستم عامل | POSIX :: Linux |
| نام فایل | ProcessedPiRecorder-0.3.1 |
| نام | ProcessedPiRecorder |
| نسخه کتابخانه | 0.3.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Matthew Davenport |
| ایمیل نویسنده | mdavenport@rockefeller.edu |
| آدرس صفحه اصلی | https://github.com/mattisabrat/ProcessedPiRecorder |
| آدرس اینترنتی | https://pypi.org/project/ProcessedPiRecorder/ |
| مجوز | GPLv3 |
# ProcessedPiRecorder
A multiprocessed wrapper of PiCamera for simplified deployment of high framerate computer vision on raspberry pi.
## Installation
pip install ProcessedPiRecorder
## Requires
Library | Version
--------|--------
tifffile | 2019.7.26
picamera | 1.13
opencv-contrib-python | 3.4.4.19
numpy | 1.17.0
imageio | 2.6.1
I'm sure it would work with other versions, but these are the ones used during dev.
## Basic Usage
You have to initialize the recorder and then tell it when to start recording.
### Initialize:
from ProcessedPiRecorder import ProcessedPiRecorder as ppr
myRecorder = ppr(tif_path=None, x_resolution=0, y_resolution=0, scale_factor=1, framerate=0,
rec_length=0, display_proc='camera_reader', stereo=False,
timestamp=False, report_Hz=False, monitor_qs= False, Hz_buffer=10,
callback=None, blocking=True, tif_compression=6,
latency_log=None, aquisition_log=None, cb_log=None)
Arg | Description
----|------------
tif_path | file to the output big tif file
(x_resolution, y_resolution) | pixel dimensions acquired by the sensor(s), is autmatically rounded to nearest multiple of 16, or nearest multiple of 32 for StereoPi x_resolution.
scale_factor | sets the resize parameter at resolultion*scale_factor, neede for StereoPi
framerate | desired framerate in Hz
rec_length | number of seconds to record
stereo | if True, sets up for the stereopi hflip=True, stereo_mode='side-by-side', stereo_decimate=False
display_proc | specifies which process should be used to display. Either 'camera_reader' or 'file_writer'.
timestamp | if True, all frames are timestapmed at aquisition
report_Hz | if True, all frames have the current frame rate stamped at aquisition
monitor_qs | if True, all frames have all queue lengths stamped at aquisition
callback | if True, execute a callback function
blocking | if True, block the main thread after spawning processes
tif_compression | specifies the degress of image compression used by tifffile
Hz_buffer | number of frames to average over when displaying framerate (report_Hz=True)
latency_log | if specified, write the latency log to path
acquisition_log | if specified, writes the acquisition log to path
cb_log | if specified, writes the callback log to path
### Start recording
myRecorder.recordVid()
## Queues and Callbacks
ProcessedPiRecorder works by separating the acquisition, computer vision, and file encoding tasks across multiple python processes using the standard python multiprocessing library. These processes pass frames using multiprocessing.Queue objects which are managed by QueueHandler objects so you don't muck them up.
### Queue Structure
### Callback structure
Computer vision can be easily added by means of a callback function. Frames are recieved from and placed into the queues using a ppr.QueueHandler object which also provides a buffer of frames for applications that require a series of frames.
import ProcessedPiRecorder as ppr
callback_fucntion(queue1, queue2, cb_queue, cb_logger):
#inits
handler = ppr.QueueHandler(queue1, queue2, 2)
#infinite loop
while True:
#get frame
frame = handler.get()
#make sure the handler has a new frame and the buffer has filled
if not handler.empty and handler.full_buffer:
#Do something
do_something_to(frame)
#Save the frame
handler.put()
Arg | Description
----|------------
queue1 | recieves frames. Let a QueueHandler deal with it
queue2 | sends frames to be saved. Let a QueueHandler deal with it
cb_queue | multiprocessing.Queue object attached to the ppr object (myRecorder.cb_queue), enables comunication between the callback and the main_process
## StereoPi support
The StereoPi is cool, but using standard PiCamera you can't save a highframerate video to file without dropping frames, ProcessedPiRecorder fixes that. Be aware that the scale_factor parameter must be used to down sample the frames. I use the following parameters as a starting point for high framerate acquisition (~28Hz) on stereopi:
x_resolution=1280, y_resolution=480, scale_factor=0.3, framerate=25
## Contributors
This code was written and is maintained by [Matt Davenport](https://github.com/mattisabrat) (mdavenport@rockefeller.edu).
نیازمندی
| مقدار | نام |
|---|---|
| ==1.13 | picamera |
| ==3.4.4.19 | opencv-contrib-python |
| ==2019.7.26 | tifffile |
| ==1.17.0 | numpy |
| ==2.6.1 | imageio |
نحوه نصب
نصب پکیج whl ProcessedPiRecorder-0.3.1:
pip install ProcessedPiRecorder-0.3.1.whl
نصب پکیج tar.gz ProcessedPiRecorder-0.3.1:
pip install ProcessedPiRecorder-0.3.1.tar.gz