Scavengers Reign Flux

세부 정보

모델 설명

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.

이 모델로 만든 이미지