Short comings of the stable diffusion model
Outlining my experience with the results of prompt to stable diffusion for educational content
Published Mar 10, 2024
My experience with partyrock was a wonderful one with the amazing set of GenAI tools which were provided.
However, my experience was blighted a little by the result of the image generation model provided . Trying to use the image generation for educational context was not promising as the model was unable to capture the essence of the prompts it was being provided with.
For example:
An intended use case was to use the model to generate an image where summarized key points from the provided study material. The following sample prompts were used
An intended use case was to use the model to generate an image where summarized key points from the provided study material. The following sample prompts were used
Foe context, the content of the summary list is:
''
- Carbon dioxide levels are at a record high
- Carbon dioxide, a key greenhouse gas that drives global climate change
- Greenhouse gases are now out of balance and threaten to change drastically which living things can survive on this planet
- Atmospheric levels of carbon dioxide are at the highest levels ever recorded
- Greenhouse gases absorb solar energy and keep heat close to Earth's surface, rather than letting it escape into space
- Climate change encompasses rising average temperatures, extreme weather events, shifting wildlife populations and habitats, rising seas, and other impacts
- Carbon dioxide is the primary greenhouse gas, responsible for about three-quarters of emissions
- Methane is a potent greenhouse gas released from landfills, natural gas and petroleum industries, and agriculture
- ''
- An blank whiteboard containing the contents of the list in [Key phrases]
The image below shows the response by the model
- A blank canvas and the list of phrases in [Key Phrases] written on the blank canvas
This exemplifies an aspect of image generation that still need further exploration and training and I await further development to see as this shortcoming can be mitigated in future models.