image processing

This commit is contained in:
Bruce MacDonald 2025-03-20 15:15:04 -07:00
parent 1eab2c85cc
commit 26767c665a
3 changed files with 76 additions and 22 deletions

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@ -1,4 +1,4 @@
package pixtral package mistral3
import ( import (
"fmt" "fmt"

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@ -1,4 +1,4 @@
package pixtral package mistral3
import ( import (
"bytes" "bytes"

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@ -1,9 +1,14 @@
package mistral3 package mistral3
import ( import (
"image"
_ "image/jpeg"
_ "image/png"
"github.com/ollama/ollama/kvcache" "github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml" "github.com/ollama/ollama/ml"
"github.com/ollama/ollama/model" "github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/imageproc"
"github.com/ollama/ollama/model/input" "github.com/ollama/ollama/model/input"
) )
@ -11,14 +16,46 @@ type Model struct {
model.Base model.Base
*TextModel *TextModel
ImageProcessor
// TODO: Add VisionModel field // TODO: Add VisionModel field
// *VisionModel `gguf:"v,vision"` // *VisionModel `gguf:"v,vision"`
// TODO: Add MultiModalProjector field for combining vision and text features // TODO: Add MultiModalProjector field for combining vision and text features
// *MultiModalProjector `gguf:"mm"` // *MultiModalProjector `gguf:"mm"`
}
// TODO: Add ImageProcessor field // Adding ImageProcessor struct
// ImageProcessor type ImageProcessor struct {
imageSize int
patchSize int
numChannels int
longestEdge int
}
// Function to create a new ImageProcessor
func newImageProcessor(c ml.Config) ImageProcessor {
return ImageProcessor{
imageSize: int(c.Uint("vision.image_size", 1024)),
patchSize: int(c.Uint("vision.patch_size", 16)),
numChannels: int(c.Uint("vision.num_channels", 3)),
longestEdge: int(c.Uint("vision.longest_edge", 1024)),
}
}
// Method to process images for the model
func (p *ImageProcessor) ProcessImage(img image.Image) ([]float32, error) {
// Get output size based on longest edge and patch size
outputSize := getResizeOutputImageSize(img, p.longestEdge, image.Point{p.patchSize, p.patchSize})
// Resize the image
newImage := imageproc.Composite(img)
newImage = imageproc.Resize(newImage, outputSize, imageproc.ResizeBilinear)
// Normalize image data
data := imageproc.Normalize(newImage, imageproc.ClipDefaultMean, imageproc.ClipDefaultSTD, true, true)
return data, nil
} }
// TODO: Implement MultimodalProcessor interface // TODO: Implement MultimodalProcessor interface
@ -32,12 +69,12 @@ func New(c ml.Config) (model.Model, error) {
m := &Model{ m := &Model{
TextModel: textModel, TextModel: textModel,
// Initialize the ImageProcessor
ImageProcessor: newImageProcessor(c),
// TODO: Initialize VisionModel if present // TODO: Initialize VisionModel if present
// VisionModel: newVisionModel(c), // VisionModel: newVisionModel(c),
// TODO: Initialize ImageProcessor
// ImageProcessor: newImageProcessor(c),
// TODO: Initialize MultiModalProjector // TODO: Initialize MultiModalProjector
// MultiModalProjector: &MultiModalProjector{...}, // MultiModalProjector: &MultiModalProjector{...},
} }
@ -47,21 +84,38 @@ func New(c ml.Config) (model.Model, error) {
return m, nil return m, nil
} }
// TODO: Implement EncodeMultimodal method for processing images // Implement EncodeMultimodal method for processing images
// func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) { func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
// // Check if vision model is available // Check if vision model exists - return error for now
// // Decode image return nil, model.ErrNoVisionModel
// // Process the image
// // Pass through vision model
// // Project vision outputs to text embedding space
// // Return vision embeddings
// }
// TODO: Implement PostTokenize method to handle vision tokens // This will be implemented when adding the vision model:
// func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) { /*
// // Add special tokens around image data image, _, err := image.Decode(bytes.NewReader(multimodalData))
// // Insert placeholders for image tokens if err != nil {
// } return nil, err
}
f32s, err := m.ImageProcessor.ProcessImage(image)
if err != nil {
return nil, err
}
pixelValues, err := ctx.Input().FromFloatSlice(f32s,
m.ImageProcessor.imageSize,
m.ImageProcessor.imageSize,
m.ImageProcessor.numChannels,
)
if err != nil {
return nil, err
}
// Will need VisionModel to process this
// visionOutputs := m.VisionModel.Forward(ctx, pixelValues)
// visionOutputs = m.MultiModalProjector.Forward(ctx, visionOutputs)
// return visionOutputs, nil
*/
}
func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) { func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs)) inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
@ -79,7 +133,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
return nil, err return nil, err
} }
// TODO: Add handling of multimodal inputs // TODO: Add handling of multimodal inputs when vision model is added
// Set image embeddings into hidden state if present in opts.Multimodal // Set image embeddings into hidden state if present in opts.Multimodal
return m.TextModel.Forward(ctx, inputs, positions, outputs, opts, m.Cache), nil return m.TextModel.Forward(ctx, inputs, positions, outputs, opts, m.Cache), nil