gemini-agentic-vision

Automating image analysis with Python requires combining visual reasoning models with dynamic code execution. This skill uses Gemini Vision to plan multi-step visual tasks, automatically writing and running Python code to crop, annotate, or extract data from images.

Detecting objects and drawing bounding boxes in UI screenshots can be achieved through autonomous visual reasoning. The skill uses Gemini to identify UI elements like buttons, then automatically executes Python code to draw bounding boxes and save the annotated image.

Autonomous image analysis with this skill requires a valid GEMINI_PAID_API_KEY environment variable. You also need the google-genai Python package installed to enable the dynamic code execution and extended thinking capabilities.

Gemini's extended thinking works for complex visual tasks by enabling an autonomous, multi-step reasoning process. Instead of immediate output, it plans the image analysis, dynamically writes Python code to process the visual data, and executes it to parse charts or annotate UI elements.

The best way to extract chart data from images into a structured format is using code-driven visual processing. This approach combines Gemini Vision to interpret the chart and dynamically executes Python code to parse and extract the visual data into JSON.