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prithivMLmods/Kontext-0811-exp
Kontext-0811-exp is a image-to-image model from prithivMLmods. Use it when you need one image transformed into another. It is set up for diffusers. The card lists the license as other.
The Kontext-0811-exp collection is a suite of fine-tuned adapters for black-forest-lab’s FLUX.1-Kontext-dev, developed to extend its visual transformation capabilities across multiple camera perspectives and enhanceme…
Downloads · 30 days
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18% of all-time downloads
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.safetensors3.7 GB · 100%
From the Hugging Face model README
The Kontext-0811-exp collection is a suite of fine-tuned adapters for black-forest-lab’s FLUX.1-Kontext-dev, developed to extend its visual transformation capabilities across multiple camera perspectives and enhancement modes. Each adapter in this set is trained for a specific spatial or stylistic transformation, ensuring high-quality, context-aware image reinterpretation without loss of realism, lighting accuracy, or environmental consistency.
Transforms a scene into a top-down perspective, maintaining accurate visual proportions, lighting consistency, and spatial relationships. Ensures that backgrounds, textures, and environmental shadows align naturally from the elevated viewpoint. Training Data: 800 image pairs (400 start, 400 end)
Generates a bottom-up perspective of the scene, preserving depth, scale, and lighting direction for enhanced realism. Adapts sky or floor elements naturally to the new viewing angle, ensuring authentic shadows and geometry consistency. Training Data: 800 image pairs (400 start, 400 end)
Produces a left-side perspective while maintaining consistent lighting, textures, and proportions. Reveals previously unseen left-side details with realistic geometry and environment coherence. Training Data: 800 image pairs (400 start, 400 end)
Generates a right-side camera perspective with natural lighting, accurate geometry, and realistic textures. Preserves harmony with the original image’s environment, shadows, and visual tone, offering seamless right-side continuation. Training Data: 800 image pairs (400 start, 400 end)
Upscales low-quality images to 4K resolution, enhancing sharpness, clarity, and fine details while maintaining original texture, color, and lighting. Effectively removes noise, blur, and compression artifacts for clean, high-fidelity results. Training Data: 1,000 image pairs (500 start, 500 end)
Reinterprets the input scene through an artistic or creative perspective, blending imagination with realism. Uses dynamic camera angles, cinematic framing, depth of field, and surreal compositions to deliver expressive yet coherent visual outputs. Training Data: 700 image pairs (350 start, 350 end)
Top-Down View
[photo content], recreate the scene from a top-down perspective. Maintain all visual proportions, lighting consistency, and realistic spatial relationships. Ensure the background, textures, and environmental shadows remain naturally aligned from this elevated angle.
Bottom-Up View
[photo content], recreate the scene from a bottom-up perspective. Preserve accurate depth, scale, and lighting direction to enhance realism. Ensure the background sky or floor elements adjust naturally to the new angle, maintaining authentic shadowing and perspective.
Left View
[photo content], render the image from the left-side perspective, keeping consistent lighting, textures, and proportions. Maintain the realism of all surrounding elements while revealing previously unseen left-side details consistent with the object’s or scene’s structure.
Right View
[photo content], generate the right-side perspective of the scene. Ensure natural lighting, accurate geometry, and realistic textures. Maintain harmony with the original image’s environment, shadows, and visual tone while providing the right-side visual continuation.
Artistic Mode
[photo content], reinterpret the scene in a creative or artistic perspective, blending imagination with realism. Experiment with dynamic camera angles, depth of field, and artistic framing — such as diagonal, cinematic, macro, or surreal top-left perspectives — while keeping visual coherence and emotional authenticity.
.safetensors