import cvas
client = cvas.client("fpfGmGL99O+3bM1BpV8vSQLeHxxocf+IeLMcKHFwfXU=",
"http://localhost:5000")
run = client.run("0ca1edcf-a535-4c5f-7048-08d4a22cf837")
print(run.std_out)
import cvas
import os
import json
from PIL import Image
filename = "grayscale-black-and-white.jpg"
client = cvas.client("siOqZKBcJ50GYwAnJYCvh0nAFXUBCg1z7tgPBP/2ib0=",
"http://localhost:5000")
uploadedFile = client.upload_file(filename)
algorithm = client.algorithm("face-detection")
arguments = {"input": uploadedFile, "outputType": "text"}
result = algorithm.run(arguments)
if result.status == "success":
print("Success, cropping...")
faces = json.loads(result.std_out)
original = Image.open(filename)
for index, face in enumerate(faces):
print(face)
cropped = original.crop(
(face['x'], face['y'], face['x'] + face['width'],
face['y'] + face['height']))
cropped.save('./result/' + str(index) + filename)
import cvas
client = cvas.client("zVes/1008G1YhtKNiNa0WY5ZGubLK+DYYu0g+e1hcmQ=",
"http://cvas.azurewebsites.net")
algorithm = client.algorithm("hello-world")
result = algorithm.run(["Hello", "Darkness", "My", "Old", "Friend"])
print("Id: " + result.object_id)
print("Result: " + result.status)
print("StdOut: " + result.std_out)
print("StdErr:" + result.std_err)
print("Duration: " + str(result.duration) + " ms")
import cvas
import sys
client = cvas.client("8bttfegqwfX5Do6rgHIF4t/5Eco7uYm8MoSrpn6p6S8=", "http://localhost:5000")
with open("C:\\Users\\adamj\\OneDrive\\Study\\DP\\AlgorithmAssets\\car1.jpg", 'rb') as readFile:
file = client.upload_data(readFile.read(), "image/jpeg", ".jpg")
if file is None:
print("Error with uploading file from data")
sys.exit(1)
print(file.object_id)
algorithm = client.algorithm("license-plate-recognition")
result = algorithm.run([{ "c" : "eu", "n": 1}, file])
while result.status == "notFinished":
result.get()
print("Result: " + result.status)
print("StdOut: " + result.std_out)
print("StdErr:" + result.std_err)
print("Duration: " + str(result.duration) + " ms")
