This book offers a comprehensive, Python-based approach to mastering Stable Diffusion for AI image generation. Unlike other resources on this topic that focus mainly on using web interfaces, Using Stable Diffusion with Python delves into the technical aspects of controlling Stable Diffusion programmatica...
The physical host is responsible for maintaining (declaring and allocating) spatially explicit arrays for all state variables exported by FABM, and all external variables required by FABM. In the case of state variables, the host must also handle advection and diffusion (if modelled), as well a...
Full Usage - Python # Initialize diffusion generatorfromcgdimportclip_guided_diffusionimportcgd_utilcgd_generator=clip_guided_diffusion(prompts=["an image of a fox in a forest"],image_prompts=["image_to_compare_with_clip.png"],batch_size=1,clip_guidance_scale=1500,sat_scale=0,tv_scale=150,...
All models for this section were implemented in Python 3.7 and PyTorch. For training, we used the Adam [43] optimizer at its default learning rate of 0.0001 (if not stated differently) with no additional weight decay. 4.4. Case studies ...
One should note that with conventional synchrotron X-ray sources the main source of radiation damage is via the generation of radicals from the solvent (water). Subsequent diffusion of these radicals leads to specific damage (for example, reduction of metal sites) and modification of amino acid ...
For crystallization, the tubulin-DARPin D1 (TD1) complex was formed by mixing the respective components in a 1:1.1 molar ratio. The TD1 complex was crystallized using EasyXtal 15-well plates by the hanging drop vapor diffusion method (drop size 2 μl, drop ratio 1:1, 8 drops per we...
However, as pointed out before, these diffusion patterns are highly dependent on which keyword we are focusing. Figure 10 (right) depicts the information spreading results when focusing on a specific one: "Nurse". In this case, the four organizations are hardly distin- guishable, with USAID ...
A recent extension applied a nonlinear kernel diffusion technique to boost relevant, complementary information in similarity matrices [49]. DTI benchmarks The most widely used DTI benchmark from Yamanishi et al. [7] defined DTI prediction as a binary prediction problem with a single source of ...
Generate images with Claude: Use Claude with Stable Diffusion for image generation. Advanced Techniques Sub-agents: Learn how to use Haiku as a sub-agent in combination with Opus. Upload PDFs to Claude: Parse and pass PDFs as text to Claude. ...
Repository for example Hierarchical Drift Diffusion Model (HDDM) code using JAGS in Python. These scripts provide useful examples for using JAGS with pyjags, the JAGS Wiener module, mixture modeling in JAGS, and Bayesian diagnostics in Python. - mdnunez/