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Scavengers Reign Style - LoRA

61

306

617

16

Verified:

SafeTensor

Type

LoRA

Stats

306

617

76

Reviews

Published

Nov 20, 2023

Base Model

SDXL 1.0

Training

Steps: 2,500
Epochs: 10

Usage Tips

Clip Skip: 1
Strength: 1

Trigger Words

Scavengers Reign Style

Hash

AutoV2
2AD55FAA9B
default creator card background decoration

jerel

Created on Civitai

This model was trained on 1000 random screenshots of the TV-show Scavengers Reign (2023) on MAX. I've used the civitai default settings for training.

Workflow

  1. I used a short Python script to grab random images from an MP4 file

  2. Then I used czkawka (github) to get rid of any duplicate or similar images

  3. After that, I checked all the images manually

  4. I used the WD14 Model within kohya_ss (github) for captioning

  5. Finally I uploaded captions and images to civitai for training

Code:

import cv2
import random

mp4_directory = ''
output_directory = ''
frames_to_extract = 120
base_name = "Random_screenshot"
list_of_random_frames = []
frame_distance = 100
first_frame = 0 

count = 0

vidcap = cv2.VideoCapture(mp4_directory)
totalFrames = vidcap.get(cv2.CAP_PROP_FRAME_COUNT)
while count < frames_to_extract:
    count += 1
    count_str = str(count)
    frames_skipped = -1
    while True:
        randomFrameNumber = random.randint(0, totalFrames)
        frames_skipped +=1
        if frames_skipped > 0:
            print(f"Frame Skipped {frames_skipped}")
        if all(abs(randomFrameNumber - frame) > frame_distance and randomFrameNumber> first_frame for frame in list_of_random_frames):
            break
    list_of_random_frames.append(randomFrameNumber)
    photo_output = output_directory + basename + count_str + ".png"
    vidcap.set(cv2.CAP_PROP_POS_FRAMES,randomFrameNumber)
    success, image = vidcap.read()
    if success:
        cv2.imwrite(photo_output, image)
    print(f"Saving image to: {photo_output}")

PS: If you want the dataset please contact me. I just don't want to get CivitAI in copyright trouble.