llama.cpp/tools/mtmd/mtmd-image.h

#pragma once

#include "ggml.h"
#include "clip-model.h"

#include <vector>
#include <string>

#define MTMD_INTERNAL_HEADER

struct mtmd_image_preproc_out {
    std::vector<clip_image_f32> entries;
    // grid size is required for llava-uhd style models

    clip_image_f32 overview; // overview image (downscaled image)
    int grid_x = 0;
    int grid_y = 0;

    void append(const clip_hparams & hparams, const clip_image_u8 & img, bool normalized = true);
    void append(const clip_hparams & hparams, const std::vector<clip_image_u8> & imgs, bool normalized = true);
    void append(const clip_hparams & hparams, clip_image_f32 & img, bool normalized = true);

    void append_overview(const clip_hparams & hparams, const clip_image_u8 & img, bool normalized = true);
    bool has_overview() const {
        return overview.nx() > 0 || overview.ny() > 0;
    }
};

// base class, models must inherit from this class
struct mtmd_image_preprocessor {
    const clip_hparams & hparams;

    mtmd_image_preprocessor(const clip_ctx * ctx): hparams(*clip_get_hparams(ctx)) {}

    virtual ~mtmd_image_preprocessor() = default;
    virtual mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const = 0;
};

/**
 * implementation of LLaVA-UHD:
 *  - https://arxiv.org/pdf/2403.11703
 *  - https://github.com/thunlp/LLaVA-UHD
 *  - https://github.com/thunlp/LLaVA-UHD/blob/302301bc2175f7e717fb8548516188e89f649753/llava_uhd/train/llava-uhd/slice_logic.py#L118
 *
 * overview:
 *   - an image always have a single overview (downscaled image)
 *   - an image can have 0 or multiple slices, depending on the image size
 *   - each slice can then be considered as a separate image
 *
 * note: the term "slice" and "tile" are used interchangeably
 *
 * for example:
 *
 * [overview] --> [slice 1] --> [slice 2]
 *           |                |
 *           +--> [slice 3] --> [slice 4]
 *
 * NOTE: for the ordering of overview, set "ov_img_first" on the mtmd_context
 */
struct mtmd_image_preprocessor_llava_uhd : mtmd_image_preprocessor {
    mtmd_image_preprocessor_llava_uhd(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;

    struct slice_coordinates {
        int x;
        int y;
        clip_image_size size;
    };

    struct slice_instructions {
        clip_image_size overview_size; // size of downscaled image
        clip_image_size refined_size;  // size of image right before slicing (must be multiple of slice size)
        clip_image_size grid_size;     // grid_size.width * grid_size.height = number of slices
        std::vector<slice_coordinates> slices;
    };

    virtual slice_instructions get_slice_instructions(const clip_image_size & original_size) const;

    struct slice_output {
        clip_image_u8 overview;
        std::vector<clip_image_u8> slices;
    };
    slice_output slice_image(const clip_image_u8 & img, const slice_instructions & inst) const;

protected:
    clip_image_size get_best_resize(const clip_image_size & original_size, int scale_resolution, int patch_size, bool allow_upscale = false) const;

    /**
     * Selects the best resolution from a list of possible resolutions based on the original size.
     *
     * For example, when given a list of resolutions:
     *  - 100x100
     *  - 200x100
     *  - 100x200
     *  - 200x200
     *
     * And an input image of size 111x200, then 100x200 is the best fit (least wasted resolution).
     *
     * @param original_size The original size of the image
     * @param possible_resolutions A list of possible resolutions
     * @return The best fit resolution
     */
    clip_image_size select_best_resolution(const clip_image_size & original_size, const std::vector<clip_image_size> & possible_resolutions) const;

private:
    clip_image_size resize_maintain_aspect_ratio(const clip_image_size & orig, const clip_image_size & target_max) const;
    int ensure_divide(int length, int patch_size) const;
    clip_image_size get_refine_size(const clip_image_size & original_size, const clip_image_size & grid, int scale_resolution, int patch_size, bool allow_upscale = false) const;
    clip_image_size get_best_grid(const int max_slice_nums, const int multiple, const float log_ratio) const;
};

// downscale or upscale the input image to fixed size
struct mtmd_image_preprocessor_fixed_size : mtmd_image_preprocessor {
    mtmd_image_preprocessor_fixed_size(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

// resize image to multiple of patch_size*n_merge, while preserving aspect ratio
// if image_resize_pad is true, the resized image will be padded, otherwise it will be either stretched or center-cropped depending on image_resize_pad
// this is used by models with native support for dynamic image size, for example: Qwen-VL, Pixtral, Kimi-VL, etc
struct mtmd_image_preprocessor_dyn_size : mtmd_image_preprocessor {
    mtmd_image_preprocessor_dyn_size(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

// GLM 5.3 flash, similar to dyn_size, but each edge is aligned up to patch_size*n_merge, and max budget is met by a search over the height with the width scaled proportionally
struct mtmd_image_preprocessor_glm5v : mtmd_image_preprocessor {
    mtmd_image_preprocessor_glm5v(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

// similar to mtmd_image_preprocessor_dyn_size, but resize the image to have longest edge equal to hparams.image_longest_edge, while preserving aspect ratio
struct mtmd_image_preprocessor_longest_edge : mtmd_image_preprocessor {
    mtmd_image_preprocessor_longest_edge(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

// ref: inference/image_processor.py in the HF repo (DeepSeek-V4-Flash-Vision)
struct mtmd_image_preprocessor_deepseek4v : mtmd_image_preprocessor {
    mtmd_image_preprocessor_deepseek4v(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;

private:
    struct grid_info {
        int n_llm_h;
        int n_llm_w;
        int n_tokens; // token count of the block (incl. newline/pad rows and start/end, excl. lead pads)
    };
    static grid_info grid_tokens(int best_height, int best_width, int patch_size, int r);
    static void solve_resize_ratio(int height, int width, int p, int r, int max_n_token, int & best_height, int & best_width);
    static void safe_resize(int height, int width, int & best_height, int & best_width, int p, int r, int max_n_token);
};

// custom llava-uhd slicing logic for MiniCPM-V
struct mtmd_image_preprocessor_minicpmv : mtmd_image_preprocessor_llava_uhd {
    using mtmd_image_preprocessor_llava_uhd::mtmd_image_preprocessor_llava_uhd;
    slice_instructions get_slice_instructions(const clip_image_size & original_size) const override;
};

// custom llava-uhd slicing logic for LFM2
// ref: https://github.com/huggingface/transformers/blob/v5.1.0/src/transformers/models/lfm2_vl/image_processing_lfm2_vl_fast.py
struct mtmd_image_preprocessor_lfm2 : mtmd_image_preprocessor_llava_uhd {
    // ref: https://huggingface.co/LiquidAI/LFM2.5-VL-1.6B/blob/main/processor_config.json
    static constexpr int   min_tiles            = 2;
    static constexpr int   max_tiles            = 10;
    static constexpr float max_pixels_tolerance = 2.0f;
    static constexpr int   tile_size            = 512;

    using mtmd_image_preprocessor_llava_uhd::mtmd_image_preprocessor_llava_uhd;
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
    slice_instructions get_slice_instructions(const clip_image_size & original_size) const override;

    static bool should_tile(const clip_hparams & hparams, const clip_image_size & original_size);

private:
    clip_image_size find_closest_aspect_ratio(
            float aspect_ratio,
            const std::vector<clip_image_size> & target_ratios,
            int width, int height) const;
    std::vector<clip_image_size> get_target_ratios() const;
    clip_image_size get_grid_layout(int height, int width) const;
};

struct mtmd_image_preprocessor_idefics3 : mtmd_image_preprocessor_llava_uhd {
    mtmd_image_preprocessor_idefics3(const clip_ctx * ctx) : mtmd_image_preprocessor_llava_uhd(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

struct mtmd_image_preprocessor_internvl : mtmd_image_preprocessor_llava_uhd {
    mtmd_image_preprocessor_internvl(const clip_ctx * ctx) : mtmd_image_preprocessor_llava_uhd(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

// DeepSeek-OCR (v1/v2) global view + optional local tile grid
struct mtmd_image_preprocessor_deepseekocr : mtmd_image_preprocessor {
    mtmd_image_preprocessor_deepseekocr(const clip_ctx * ctx)
        : mtmd_image_preprocessor(ctx),
            fuse_row(clip_get_projector_type(ctx) == PROJECTOR_TYPE_DEEPSEEKOCR),
          base_size(hparams.image_size),
          tile_size(hparams.preproc_tile_size),
          min_tiles(hparams.preproc_min_tiles),
          max_tiles(hparams.preproc_max_tiles) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;

private:
    bool fuse_row; // v1 fuses a tile-row into one image; v2 keeps tiles separate
    int base_size; // global view
    int tile_size; // each tile
    int min_tiles;
    int max_tiles;

    std::vector<clip_image_size> get_target_ratios() const;
    clip_image_size find_closest_aspect_ratio(
            float aspect_ratio,
            const std::vector<clip_image_size> & target_ratios,
            int width, int height) const;
};

// custom image preprocessing for Step3VL
// ref: https://huggingface.co/stepfun-ai/Step3-VL-10B/blob/main/processing_step3.py
struct mtmd_image_preprocessor_step3vl : mtmd_image_preprocessor_llava_uhd {
    mtmd_image_preprocessor_step3vl(const clip_ctx * ctx) : mtmd_image_preprocessor_llava_uhd(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
    static slice_instructions build_slice_instructions(const clip_hparams & params, const clip_image_size & prepared_size);

private:
    static constexpr int   default_image_longest_edge = 3024;
    static constexpr int   default_image_crop_size    = 504;
    static constexpr float small_aspect_ratio_limit   = 1.5f;
    static constexpr float wide_aspect_ratio_limit    = 4.0f;
    static constexpr float crop_rounding_threshold    = 0.2f;

    void img_u8_resize_bilinear_to_f32(
            const clip_image_u8 & src,
            clip_image_f32 & dst,
            int target_width,
            int target_height,
            const float mean[3],
            const float std[3]) const;
    static int get_image_longest_edge(const clip_hparams & params);
    static int determine_window_size(const clip_hparams & params, int longer, int shorter);
    static int calc_crop_extent(int length, int window_size);
    static std::vector<int> calc_grid(int length, int window_size);
    static clip_image_u8 prepare_image(const clip_image_u8 & img, const clip_hparams & params);
    static clip_image_u8 crop_with_black_padding(const clip_image_u8 & image, int x, int y, int w, int h);
};

struct mtmd_image_preprocessor_youtuvl : mtmd_image_preprocessor {
    mtmd_image_preprocessor_youtuvl(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

// llava-next "anyres": stacks the overview and all tiles into one image, assembled by clip in a single graph
struct mtmd_image_preprocessor_granite : mtmd_image_preprocessor_llava_uhd {
    mtmd_image_preprocessor_granite(const clip_ctx * ctx) : mtmd_image_preprocessor_llava_uhd(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};

// pick the patch grid closest to the input aspect ratio under the per-image token cap, stretch-resize.
struct mtmd_image_preprocessor_muse_glimmer : mtmd_image_preprocessor {
    mtmd_image_preprocessor_muse_glimmer(const clip_ctx * ctx) : mtmd_image_preprocessor(ctx) {}
    mtmd_image_preproc_out preprocess(const clip_image_u8 & img) const override;
};