from pipeline import BuildDataset

videos_and_labels = [
    # (file name in base_path, label) where label is 1 for kissing and 0 for not kissing
    ('movies_casino_royale_2006_kissing_1.mp4', 1),
    ('movies_casino_royale_2006_kissing_2.mp4', 1),
    ('movies_casino_royale_2006_kissing_3.mp4', 1),
    ('movies_casino_royale_2006_not_1.mp4', 0),
    ('movies_casino_royale_2006_not_2.mp4', 0),
    ('movies_casino_royale_2006_not_3.mp4', 0),
    
    ('movies_goldeneye_1995_kissing_1.mp4', 1),
    ('movies_goldeneye_1995_kissing_2.mp4', 1),
    ('movies_goldeneye_1995_kissing_3.mp4', 1),
    ('movies_goldeneye_1995_not_1.mp4', 0),
    ('movies_goldeneye_1995_not_2.mp4', 0),
    ('movies_goldeneye_1995_not_3.mp4', 0),
]

builder = BuildDataset(base_path='path/to/movies',
                 videos_and_labels=videos_and_labels,
                 output_path='/path/to/output',
                 test_size=1 / 3)  # set aside 1 / 3 of data for validation
builder.build_dataset()

from segmentor import Segmentor
import utils

# download model.pkl from https://drive.google.com/file/d/1RlvvdInTXtJikGv_ZbHcKoblCypN1Z0A/view?usp=sharing
# or train your own
model = utils.unpickle('model.pkl')  # pickled PyTorch model 
s = Segmentor(model, min_frames=10, threshold=0.7)

# For YouTube clip Hot Summer Nights - Kiss Scene (Maika Monroe and Timothee Chalamet)
# at https://www.youtube.com/watch?v=GG5HmLQ_Fx0
# v=XXX is the YouTube ID, pass that here 
s.visualize_segments_youtube('GG5HmLQ_Fx0')

# alternatively you can provide a path to a local mp4 file
s.visualize_segments('path/to/file.mp4')