import msu_vqmt
vqmt = msu_vqmt.find()

import msu_vqmt

try :
    vqmt = msu_vqmt.find()
except Exception as e:
    print('Unable to find or load VQMT: %s' % str(e))
    exit(1)
    
vqmt_ver = vqmt.getVersionObject()
print('Found MSU VQMT %d.%d' % (vqmt_ver.maj, vqmt_ver.min))

import msu_vqmt
vqmt = msu_vqmt.loadByDir(your_vqmt_path)

import msu_vqmt

# replace the following line if you have portable installation:
vqmt = msu_vqmt.find()

if not vqmt.isActivated():
    # premium activation:
    result = vqmt.activate_premium(yout_premium_code)
    
    # or pro activation:
    result = vqmt.activate_pro(your_pro_code)
    
    if not result:
        print('Could not activate VQMT: %s' % vqmt.getError())
    else:
        print('Activation passed')

import msu_vqmt
import json
vqmt = msu_vqmt.find()

# creating configuration
config = msu_vqmt.Config()
config.addMetric('psnr', component='Y')
config.addFile('/path/to/source.mp4')
config.addFile('/path/to/dist.mp4', startFrame=10, endFrame=20)

# running configuration
invoke = vqmt.invoke(config)
invoke.start()

# printing results
print(json.dumps(invoke.getColumns(), indent=2))       # columns of values table
print(invoke.getFrameNumbersAsArray())                 # returns numpy array
print(invoke.getValuesAsArray())                       # returns numpy matrix
print(json.dumps(invoke.getAccumulators(), indent=2))  # accumulators

# creating vqmt and config...

invoke = vqmt.invoke(config)
if not invoke:
	print(invoke.getInitError())
	sys.exit(1)
	
# running invoke..

import msu_vqmt
import json
import time

vqmt = msu_vqmt.find()

# add a lot of metrics
config = msu_vqmt.Config()
for c in list('YUVRGBL') + ['YUV', 'RGB']:
	config.addMetric('psnr', component=c)
for c in list('YUVRGB'):
	config.addMetric('ssim', component=c)
	config.addMetric('msssim', component=c)
config.addMetric('vmaf', component='Y')

# and some files
config.addFile('original.mp4')
config.addFile('distorted.mp4')

# running configuration
invoke = vqmt.invoke(config)
invoke.startAsynch()

# wait initialization
invoke.waitPrepareComplete()
print('Initialization complete')

# printing information about files and metrics
print(json.dumps(invoke.getColumns(), indent=2))
print(json.dumps(invoke.getFiles(), indent=2))

# let VQMT run for 1s
time.sleep(1)
invoke.pause()

# give it time to rest and then resume
print('Pause 3 sec.')
time.sleep(3)

print('Resuming')
invoke.resume()

# finally wait for the end and print results
invoke.wait()
print('Complete measure')
print(json.dumps(invoke.getAccumulators(), indent=2))

def value_cb(invoke, frame, col, val): 
    print('Frame %d col %d: %f' % (frame, col, val))
    
def event_cb(data):
	print(json.dumps(data,indent=2))

# creating vqmt and config...

# running measure
invoke = vqmt.invoke(config, event_cb, value_cb)
invoke.start()

import msu_vqmt
import json

vqmt = msu_vqmt.find()

config = msu_vqmt.Config()

# adding files with different reslution and a metric
config.addFile('../media/sunflower720.mp4')
config.addFile('../media/sunflower540.mp4')
config.addMetric('psnr', component='Y')

# vqmt will fail because geometry correction is disabled by default
invoke = vqmt.invoke(config)
invoke.start()
assert invoke.getExitStatus() == 200  # Status 200 - failed


# create another configuration with enabled geometry
config_data = {
    # configuring visualization
    'vis': {
        'enabled': True,
        'output_directory': '/vis/path',
        'compressor': 'h264'
    },
    # enabling input image resize
    'geometry': {
        'enabled': True
    },
    # configuring concurrency
    'performance': {
        'threads_number': 2,
        'metric_parallelism': 2
    }
}
config = msu_vqmt.Config(config_data)

# adding files with different reslution and a metric
config.addFile('../media/sunflower720.mp4')
config.addFile('../media/sunflower540.mp4')
config.addMetric('psnr', component='Y')

# now should be ok
invoke = vqmt.invoke(config)
invoke.start()
assert invoke.getExitStatus() == 100  # Status 100 - OK

import msu_vqmt
import json
import numpy as np

vqmt = msu_vqmt.find()

# the callback will be invoked as soon as a frame is needed
def input_cb(invoke_id, file, frame, data, chan_mask):
    # return None for error
    if file not in ['file1', 'file2']: return       
        
    # return False for EOF
    if frame >= 10: return False 

    # create solid image
    multiplier = 10 if file == 'file1' else 8
    img = np.ndarray([1280,720], dtype=np.ubyte)
    img.fill(50 + frame * multiplier)
    
    # copy image to VQMT buffer
    vqmt.copyImage(img, data, chan_mask)
    
    # return True for success
    return True

config = msu_vqmt.Config()

# Adding two files. We specified fmt gray to have monochrome frames.
# It's possible to use any picture type from 
# https://videoprocessing.ai/vqmt/online-help-last/picture-types/
config.addFile("file1", mode="callback", 
               props={"frames":10, "fmt":"gray", "w": 1280, "h": 720})
config.addFile("file2", mode="callback", 
               props={"frames":10, "fmt":"gray", "w": 1280, "h": 720})

# adding metrics
config.addMetric('psnr', component='Y')
config.addMetric('ssim', component='Y')

# setting up invoke object and running
invoke = vqmt.invoke(config)
invoke.setInputCallback(input_cb)
invoke.start()

# printing results
print("Columns:")
print(json.dumps(invoke.getColumns(), indent=2))
print("\n\nComputed values:")
frames = invoke.getFrameNumbersAsArray()
values = invoke.getValuesAsArray()
print(np.column_stack((frames,values)))
print("\n\nAccumulators:")
print(json.dumps(invoke.getAccumulators(), indent=2))

import msu_vqmt
import json

vqmt = msu_vqmt.find()
print(json.dumps(vqmt.getVersion(), indent=2), end='\n\n')
print("1st Picture type")
print(json.dumps(vqmt.getPictureTypes()[0], indent=2), end='\n\n')
print("1st Colorspace")
print(json.dumps(vqmt.getColorspaces()[0], indent=2), end='\n\n')
print("1st Device")
print(json.dumps(vqmt.getDevices()[0], indent=2), end='\n\n')
print("1st Metric")
print(json.dumps(vqmt.getMetrics()[0], indent=2))