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missing param and updated readme

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blakeblackshear 2019-03-27 06:55:32 -05:00
parent a26d2217d4
commit a074945394
2 changed files with 13 additions and 6 deletions
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13
README.md
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@ -108,19 +108,26 @@ sensor:
- Use SSDLite models to reduce CPU usage - Use SSDLite models to reduce CPU usage
## Future improvements ## Future improvements
- [ ] Build tensorflow from source for CPU optimizations - [x] Remove motion detection for now
- [ ] Try running object detection in a thread rather than a process
- [x] Implement min person size again
- [ ] Switch to a config file
- [ ] Handle multiple cameras in the same container
- [ ] Simplify motion detection (check entire image against mask)
- [ ] See if motion detection is even worth running
- [ ] Scan for people across entire image rather than specfic regions
- [ ] Dynamically resize detection area and follow people
- [ ] Add ability to turn detection on and off via MQTT - [ ] Add ability to turn detection on and off via MQTT
- [ ] MQTT motion occasionally gets stuck ON - [ ] MQTT motion occasionally gets stuck ON
- [ ] Output movie clips of people for notifications, etc. - [ ] Output movie clips of people for notifications, etc.
- [ ] Integrate with homeassistant push camera - [ ] Integrate with homeassistant push camera
- [ ] Merge bounding boxes that span multiple regions - [ ] Merge bounding boxes that span multiple regions
- [ ] Switch to a config file
- [ ] Allow motion regions to be different than object detection regions - [ ] Allow motion regions to be different than object detection regions
- [ ] Implement mode to save labeled objects for training - [ ] Implement mode to save labeled objects for training
- [ ] Try and reduce CPU usage by simplifying the tensorflow model to just include the objects we care about - [ ] Try and reduce CPU usage by simplifying the tensorflow model to just include the objects we care about
- [ ] Look into GPU accelerated decoding of RTSP stream - [ ] Look into GPU accelerated decoding of RTSP stream
- [ ] Send video over a socket and use JSMPEG - [ ] Send video over a socket and use JSMPEG
- [ ] Look into neural compute stick - [x] Look into neural compute stick
## Building Tensorflow from source for CPU optimizations ## Building Tensorflow from source for CPU optimizations
https://www.tensorflow.org/install/source#docker_linux_builds https://www.tensorflow.org/install/source#docker_linux_builds

6
detect_objects.py
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@ -29,9 +29,9 @@ MQTT_USER = os.getenv('MQTT_USER')
MQTT_PASS = os.getenv('MQTT_PASS') MQTT_PASS = os.getenv('MQTT_PASS')
MQTT_TOPIC_PREFIX = os.getenv('MQTT_TOPIC_PREFIX') MQTT_TOPIC_PREFIX = os.getenv('MQTT_TOPIC_PREFIX')
REGIONS = "300,0,0,2000,200,no-mask-300.bmp:300,300,0,2000,200,no-mask-300.bmp:300,600,0,2000,200,no-mask-300.bmp:300,900,0,2000,200,no-mask-300.bmp" # REGIONS = "300,0,0,2000,200,no-mask-300.bmp:300,300,0,2000,200,no-mask-300.bmp:300,600,0,2000,200,no-mask-300.bmp:300,900,0,2000,200,no-mask-300.bmp:300,0,300,2000,200,no-mask-300.bmp:300,300,300,2000,200,no-mask-300.bmp:300,600,300,2000,200,no-mask-300.bmp:300,900,300,2000,200,no-mask-300.bmp"
# REGIONS = "400,350,250,50" # REGIONS = "400,350,250,50"
# REGIONS = os.getenv('REGIONS') REGIONS = os.getenv('REGIONS')
DEBUG = (os.getenv('DEBUG') == '1') DEBUG = (os.getenv('DEBUG') == '1')
@ -145,7 +145,7 @@ def main():
best_person_frame.start() best_person_frame.start()
# start a thread to parse objects from the queue # start a thread to parse objects from the queue
object_parser = ObjectParser(object_queue, objects_parsed, DETECTED_OBJECTS) object_parser = ObjectParser(object_queue, objects_parsed, DETECTED_OBJECTS, regions)
object_parser.start() object_parser.start()
# start a thread to expire objects from the detected objects list # start a thread to expire objects from the detected objects list
object_cleaner = ObjectCleaner(objects_parsed, DETECTED_OBJECTS) object_cleaner = ObjectCleaner(objects_parsed, DETECTED_OBJECTS)