Scavengers Reign Flux版本v2.0 (ID: 747404)

This model was trained on 209 random screenshots from the TV-show Scavengers Reign (2023) on MAX. I've used GPT-4o for captioning.
I've
I've kept most of the default settings of the 24gb LoRA config except for the steps which I've set to 4.000 steps.

Workflow

1. I used a short Python script to grab a 1.000 random images from a MP4 file

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

3. I've made a list of all charactes appearances, removing those that appeared the most often to avoid biases within the model

4. After that, I checked all the images manually and picked the 209 most aesthetic

5. I used a custom GPT (scavengers reign GPT) for captioning

6. Finally I've trained the model with ostris ai-toolkit (github).

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 + base_name + 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.

描述:

训练词语: Flat Art