Recent Releases of maestro
maestro - maestro-1.0.0
🚀 Added
The VLMs field is evolving rapidly, making it tough to keep up. Maestro currently supports Florence-2, PaliGemma 2, and Qwen2.5-VL, and we'll strive to add key VLMs ASAP.
VLMs fine-tuning can be costly. Maestro's built-in support for LoRA, QLoRA, and graph freezing allows training larger models even on less powerful hardware.
VLMs fine-tuning requires lots of code. Maestro simplifies this complexity with single CLI/SDK calls.
VLMs lack a unified approach. Maestro uses a consistent input format (JSONL now, COCO and YOLO coming soon) to minimize data formatting headaches.
🏆 Contributors
@onuralpszr (Onuralp SEZER), @SkalskiP (Piotr Skalski)
- Python
Published by SkalskiP about 1 year ago
maestro - multimodal-maestro-0.1.0
multimodal-maesto is out 🔥 🔥 🔥
🚀 Added
SegmentAnythingMarkGeneratorallowing the generation of segmentation marks.MarkVisualizerallowing to visualize the generated marks.prompt_imageallowing for convenient GPT-4 Vision API querying.- 🤗 Hugging Face Set-of-Mark space.
```python
import cv2 import torch import multimodalmaesto as mm
image = cv2.imread("...")
generator = mm.SegmentAnythingMarkGenerator() visualizer = mm.MarkVisualizer()
marks = generator.generate(image=image) marks = mm.refine_marks(marks=marks)
imageprompt = visualizer.visualize(image=image, marks=marks) textprompt = "Find dog."
response = mm.promptimage(apikey=apikey, image=imageprompt, prompt=text_prompt) response
"The dog is prominently featured in the center of the image with the label [9]."
masks = mm.extractrelevantmasks(text=response, detections=refined_marks)
{'6': array([ [False, False, False, ..., False, False, False], [False, False, False, ..., False, False, False], [False, False, False, ..., False, False, False], ..., [ True, True, True, ..., False, False, False], [ True, True, True, ..., False, False, False], [ True, True, True, ..., False, False, False]]) } ```
🏆 Contributors
@SkalskiP @deependujha
- Python
Published by SkalskiP about 2 years ago