description: <p>This model was trained on 209 random screenshots from the TV-show Scavengers Reign (2023) on MAX. I've used GPT-4o for captioning. <br />I've <br />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.</p><p></p><p>Workflow</p><ol><li><p>I used a short Python script to grab a 1.000 random images from a MP4 file</p></li><li><p>Then I used czkawka (<a target="_blank" rel="ugc" href="https://github.com/qarmin/czkawka">github</a>) to get rid of any duplicate or similar images</p></li><li><p>After that, I checked all the images manually and picked the 209 most aesthetic</p></li><li><p>I used a custom GPT (<a target="_blank" rel="ugc" href="https://chatgpt.com/g/g-jigGyrMzl-scavengers-reign-captioner">scavengers reign GPT</a>) for captioning</p></li><li><p>Finally I've trained the model with ostris ai-toolkit (<a target="_blank" rel="ugc" href="https://github.com/ostris/ai-toolkit">github</a>).</p></li></ol><p>Code:</p><pre><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 &lt; 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 &gt; 0:
              print(f"Frame Skipped {frames_skipped}")
          if all(abs(randomFrameNumber - frame) &gt; frame_distance and randomFrameNumber&gt; 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}")</code></pre>
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modelVersions.trainedWords: Flat Art
name: Scavengers Reign Flux
tags: anime tv show style illustration flat art