{
 "cells": [
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How To: Refine Noisy Detection Boundaries\n",
    "\n",
    "After detection, colony masks often have ragged edges, small holes, or\n",
    "spurious fragments. Use refiners to clean up the mask before measuring."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from phenotypic.data import load_yeast_plate\n",
    "from phenotypic.enhance import GaussianBlur, CLAHE\n",
    "from phenotypic.detect import OtsuDetector\n",
    "from phenotypic.refine import (\n",
    "    MaskOpener, MaskFill, SmallObjectRemover, BorderObjectRemover,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plate = load_yeast_plate()\n",
    "plate = GaussianBlur(sigma=2.0).apply(plate)\n",
    "plate = CLAHE(clip_limit=0.01).apply(plate)\n",
    "plate = OtsuDetector().apply(plate)\n",
    "print(f\"Before refinement: {plate.num_objects} objects\")\n",
    "plate.dash(overlay=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Remove Border Objects\n",
    "\n",
    "Colonies touching the image edge are usually partial. Remove them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plate = BorderObjectRemover(border_size=1).apply(plate)\n",
    "print(f\"After border removal: {plate.num_objects} objects\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Remove Small Objects\n",
    "\n",
    "Noise fragments smaller than real colonies. Set `min_size` to the\n",
    "smallest colony area you expect (in pixels)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plate = SmallObjectRemover(min_size=50).apply(plate)\n",
    "print(f\"After small object removal: {plate.num_objects} objects\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Morphological Opening\n",
    "\n",
    "Smooths jagged mask edges and breaks thin bridges between touching\n",
    "colonies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plate = MaskOpener(width=5).apply(plate)\n",
    "print(f\"After opening: {plate.num_objects} objects\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fill Holes\n",
    "\n",
    "Some detectors leave holes inside colony masks. `MaskFill` fills them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plate = MaskFill().apply(plate)\n",
    "plate.dash(overlay=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## In a Pipeline\n",
    "\n",
    "Chain these refiners after detection in your pipeline:\n",
    "\n",
    "```python\n",
    "pipeline = pht.ImagePipeline(ops=[\n",
    "    GaussianBlur(sigma=2.0),\n",
    "    CLAHE(clip_limit=0.01),\n",
    "    OtsuDetector(),\n",
    "    BorderObjectRemover(),\n",
    "    SmallObjectRemover(min_size=50),\n",
    "    MaskOpener(width=5),\n",
    "    MaskFill(),\n",
    "])\n",
    "```"
   ]
  }
 ],
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