A collection of my favorite shots out of 50,000+ images generated across various projects in 2025

Creating quality AI videos relies primarily on generating exceptional still images, which later get used in a separate image-to-video process. I found that using popular paid service image generation tools, or even untuned open source models, always yielded outputs that looked more like a stock photo than a still from a movie. It doesn't matter if the words "cinematic" and "shallow depth of field" are used in the prompt; the base models sample from vast datasets, hundreds of millions of images - more than a single person can ever see in their lifetime - resulting in outputs that feel too much like a "collective average" of every image ever made. It's like mixing all the colors of paint on a palette and ending up with some form of dull brown or grey.The, lighting, characters, compositions, and fine grain textures in this reel were only possible with a combination of LoRAs I trained thanks to open source repositories like Hugging Face, GitHub, and Civitai. I conducted extensive A/B tests in ComfyUI, locking seeds and testing model strength combinations down the hundredth of a percent, sometimes stacking 10 LoRAs together at a time, then making X/Y grids of every scheduling + sampling combination across multiple guidance scales.