emadehsan

# register this function, so JS code could call this
output.register_callback('notebook.run_algo', run_algo)

# put the JS code in cell and run it
take_photo()

emadehsan

import IPython
import time
import sys
import numpy as np
import cv2
import base64
import logging

from google.colab import output
from PIL import Image

emadehsan

from IPython.display import display, Javascript
from google.colab.output import eval_js
from base64 import b64decode

def take_photo(filename='photo.jpg', quality=0.8):
    js = Javascript('''
        // ...
        // JavaScript code here <<==
        // ...
        ''')

emadehsan

async function takePhoto(quality) {
    // create html elements
    const div = document.createElement('div');
    const video = document.createElement('video');
    video.style.display = 'block';

    // request the stream. This will ask for Permission to access 
    // a connected Camera/Webcam
    const stream = await navigator.mediaDevices.getUserMedia({video: true});

emadehsan

Processing 1 images
image                    shape: (425, 640, 3)         min:    0.00000  max:  255.00000  uint8
molded_images            shape: (1, 1024, 1024, 3)    min: -123.70000  max:  151.10000  float64
image_metas              shape: (1, 93)               min:    0.00000  max: 1024.00000  float64
anchors                  shape: (1, 261888, 4)        min:   -0.35390  max:    1.29134  float32

emadehsan

# Load a random image from the images folder
file_names = next(os.walk(IMAGE_DIR))[2]
image = skimage.io.imread(os.path.join(IMAGE_DIR, random.choice(file_names)))

# Run detection
results = model.detect([image], verbose=1)

# Visualize results
r = results[0]
visualize.display_instances(image, r['rois'], r['masks'], r['class_ids'], 

emadehsan

# Create model object in inference mode.
model = modellib.MaskRCNN(mode="inference", model_dir=MODEL_DIR, config=config)

# Load weights trained on MS-COCO
model.load_weights(COCO_MODEL_PATH, by_name=True)

emadehsan

import os
import sys
import random
import math
import numpy as np
import skimage.io
import matplotlib
import matplotlib.pyplot as plt

# Root directory of the project

emadehsan

async function takePhoto(quality) {
    // create html elements
    const div = document.createElement('div');
    const video = document.createElement('video');
    video.style.display = 'block';

    // request the stream. This will ask for Permission to access 
    // a connected Camera/Webcam
    const stream = await navigator.mediaDevices.getUserMedia({video: true});

emadehsan

In the Tests tab of your request, type this code

let cookie = postman.getResponseHeader("Set-Cookie");
postman.setEnvironmentVariable("cookie", cookie);

This will set an environment vairable. In all the requests that need cookie, add to the Request Header

Key: Cookie