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@@ -31,6 +31,7 @@ Run the container with
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docker run --rm \
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-v <path_to_frozen_detection_graph.pb>:/frozen_inference_graph.pb:ro \
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-v <path_to_labelmap.pbtext>:/label_map.pbtext:ro \
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+-v <path_to_config_dir>:/config:ro \
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-p 5000:5000 \
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-e RTSP_URL='<rtsp_url>' \
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-e REGIONS='<box_size_1>,<x_offset_1>,<y_offset_1>,<min_person_size_1>,<min_motion_size_1>,<mask_file_1>:<box_size_2>,<x_offset_2>,<y_offset_2>,<min_person_size_2>,<min_motion_size_2>,<mask_file_2>' \
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@@ -60,6 +61,19 @@ Example docker-compose:
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DEBUG: "0"
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```
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+Here is an example `REGIONS` env variable:
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+`350,0,300,5000,200,mask-0-300.bmp:400,350,250,2000,200,mask-350-250.bmp:400,750,250,2000,200,mask-750-250.bmp`
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+
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+First region broken down (all are required):
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+- `350` - size of the square (350px by 350px)
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+- `0` - x coordinate of upper left corner (top left of image is 0,0)
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+- `300` - y coordinate of upper left corner (top left of image is 0,0)
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+- `5000` - minimum person bounding box size (width*height for bounding box of identified person)
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+- `200` - minimum number of changed pixels to trigger motion
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+- `mask-0-300.bmp` - a bmp file with the masked regions as pure black, must be the same size as the region
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+
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+Mask files go in the `/config` directory.
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+
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Access the mjpeg stream at http://localhost:5000
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## Integration with HomeAssistant
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@@ -102,6 +116,7 @@ sensor:
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- [ ] Try and reduce CPU usage by simplifying the tensorflow model to just include the objects we care about
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- [ ] Look into GPU accelerated decoding of RTSP stream
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- [ ] Send video over a socket and use JSMPEG
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+- [ ] Look into neural compute stick
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## Building Tensorflow from source for CPU optimizations
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https://www.tensorflow.org/install/source#docker_linux_builds
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blakeblackshear