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#!/bin/bash | |
count=0 | |
if [ $# -ne 2 ]; then | |
>&2 echo "Usage: $0 <input_file> <output_dir>" | |
>&2 echo "This script downloads all the tar files listed in the text file from https://ai.facebook.com/datasets/segment-anything-downloads/" | |
>&2 echo "To use this, accept the terms there, download the text file and run this script with it" | |
exit 1 | |
fi |
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<?xml version="1.0" encoding="UTF-8"?> | |
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd"> | |
<plist version="1.0"> | |
<dict> | |
<key>BackgroundColor</key> | |
<data> | |
YnBsaXN0MDDUAQIDBAUGBwpYJHZlcnNpb25ZJGFyY2hpdmVyVCR0b3BYJG9iamVjdHMS | |
AAGGoF8QD05TS2V5ZWRBcmNoaXZlctEICVRyb290gAGjCwwTVSRudWxs0w0ODxAREldO | |
U1doaXRlXE5TQ29sb3JTcGFjZVYkY2xhc3NNMCAwLjg5OTk5OTk4ABADgALSFBUWF1ok | |
Y2xhc3NuYW1lWCRjbGFzc2VzV05TQ29sb3KiFhhYTlNPYmplY3QIERokKTI3SUxRU1dd |
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import streamlit as st | |
#CameraThread is a sub-class of threading.Thread | |
@st.cache(allow_output_mutation=True) | |
def get_or_create_camera_thread(): | |
for th in threading.enumerate(): | |
if th.name == 'CameraThread': | |
th.stop() | |
th.join() | |
cw = CameraThread(name='CameraThread') |
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import threading | |
import numpy as np | |
import cv2 | |
class CameraThread(threading.Thread): | |
def __init__(self, name='CameraThread'): | |
super().__init__(name=name, daemon=True) | |
self.stop_event = False | |
self.open_camera() | |
self.setup_inference_engine() |
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import streamlit as st | |
import cv2 | |
import tflite_runtime.interpreter as tflite | |
import numpy as np | |
import threading | |
from zipfile import ZipFile | |
BOX_COLOR = (0, 255, 255) #Yellow | |
TF_LITE_MODEL = './lite-model_ssd_mobilenet_v1_1_metadata_2.tflite' | |
CLASSES_OF_INTEREST = ['person', 'car', 'cat', 'dog'] |
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<div> | |
<div style="position:relative;padding-top:56.25%"> | |
<iframe src="<youtube-embed-url-here" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe> | |
</div> | |
</div> |
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#!/usr/bin/env bash | |
if [ "$#" -ne 1 ]; then | |
echo "Usage download_dataset <path_to_save>" | |
exit 1 | |
fi | |
SCRIPT_PATH="$( cd "$(dirname "$0")" ; pwd -P )" | |
TEMP_DIR=`mktemp -d 2>/dev/null || mktemp -d -t 'mytmpdir'` | |
echo $SCRIPT_PATH |
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import os, argparse | |
import tensorflow as tf | |
from tensorflow.python.framework import graph_util | |
dir = os.path.dirname(os.path.realpath(__file__)) | |
def freeze_graph(model_folder, output_nodes='y_hat', | |
output_filename='frozen-graph.pb', | |
rename_outputs=None): |
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SET(CMAKE_SYSTEM_NAME Linux) | |
SET(CMAKE_SYSROOT /path/to/rootfs) | |
#debian dependencies required for building: | |
# libpthread-stubs0-dev_0.3-2_armel.deb | |
# libx11-6_1.3.3-4+squeeze1_armel.deb | |
# libx11-dev_1.3.3-4+squeeze1_armel.deb | |
# libxau-dev_1.0.6-1_armel.deb | |
# libxcb1_1.6-1+squeeze1_armel.deb |