dip-practical/precompute.py at main · divyamohan1993/dip-practical · GitHub

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"""
Pre-compute all default practical outputs and save as static JSON cache.
Run this once at deploy time: python precompute.py
Results are served as static files — zero server computation at runtime.
"""

import json
import os
import sys

sys.path.insert(0, os.path.dirname(__file__))

from app.processors.common import get_chapter_images, ensure_chapter
from app.processors import (
    p01_display, p02_downsampling, p03_negation_subtraction,
    p04_gamma, p05_histogram_eq, p06_histogram_matching,
    p07_convolution, p08_filtering,
)

CACHE_DIR = os.path.join(os.path.dirname(__file__), "app", "static", "cache")
os.makedirs(CACHE_DIR, exist_ok=True)

DEFAULT_CHAPTER = 'CH02'


def save(name, data):
    path = os.path.join(CACHE_DIR, f"{name}.json")
    with open(path, "w") as f:
        json.dump(data, f)
    size_kb = os.path.getsize(path) / 1024
    print(f"  {name}.json ({size_kb:.0f} KB)")


def main():
    # Ensure default chapter is downloaded
    ensure_chapter(DEFAULT_CHAPTER)
    images = get_chapter_images(DEFAULT_CHAPTER)
    if not images:
        print("ERROR: No images found. Check network/dataset availability.")
        return

    # Default images
    cameraman = next((i["filename"] for i in images if "cameraman" in i["filename"]), images[0]["filename"])
    body_scan = next((i["filename"] for i in images if "partial_body" in i["filename"]), images[0]["filename"])
    einstein_low = next((i["filename"] for i in images if "einstein low" in i["filename"]), images[0]["filename"])
    angio_mask = next((i["filename"] for i in images if "angiography_mask" in i["filename"]), None)
    angio_live = next((i["filename"] for i in images if "angiography_live" in i["filename"]), None)
    skull = next((i["filename"] for i in images if "ctskull" in i["filename"]), images[1]["filename"])
    galaxy = next((i["filename"] for i in images if "galaxy" in i["filename"]), images[2]["filename"])
    dental = next((i["filename"] for i in images if "dental_xray).tif" in i["filename"]), images[3]["filename"])

    ch = DEFAULT_CHAPTER
    print(f"Dataset: {len(images)} images from {ch}")
    print(f"Defaults: {cameraman}, {body_scan}, {einstein_low}")
    print()

    # === Practical 1 ===
    print("Practical 1: Display")
    save("p1_display", p01_display.display_image(cameraman, chapter=ch))
    save("p1_histogram", p01_display.display_histogram(cameraman, chapter=ch))
    save("p1_multi", p01_display.display_multiple([
        {"chapter": ch, "filename": cameraman},
        {"chapter": ch, "filename": skull},
        {"chapter": ch, "filename": dental},
        {"chapter": ch, "filename": galaxy},
    ]))

    # === Practical 2 ===
    print("Practical 2: Downsampling")
    save("p2_downsample", p02_downsampling.downsample_series(cameraman, chapter=ch, steps=5))
    save("p2_comparison", p02_downsampling.downsample_comparison_plot(cameraman, chapter=ch))
    save("p2_upscale", p02_downsampling.upscale_comparison_plot(cameraman, chapter=ch))

    # === Practical 3 ===
    print("Practical 3: Negation/Subtraction")
    save("p3_negate", p03_negation_subtraction.compute_negation(body_scan, chapter=ch))
    if angio_mask and angio_live:
        save("p3_subtract", p03_negation_subtraction.compute_subtraction(angio_mask, angio_live, chapter1=ch, chapter2=ch))
        save("p3_pipeline", p03_negation_subtraction.compute_pipeline(angio_mask, angio_live, chapter1=ch, chapter2=ch))

    # === Practical 4 ===
    print("Practical 4: Gamma")
    save("p4_gamma", p04_gamma.apply_gamma(einstein_low, chapter=ch, gamma=0.4))
    save("p4_series", p04_gamma.gamma_series(einstein_low, chapter=ch))
    save("p4_curves", p04_gamma.transformation_curves())
    save("p4_log", p04_gamma.log_transform(einstein_low, chapter=ch))
    save("p4_contrast", p04_gamma.contrast_enhancement(einstein_low, chapter=ch, mode="dark"))

    # === Practical 5 ===
    print("Practical 5: Histogram Equalization")
    save("p5_original_histogram", p05_histogram_eq.compute_original_histogram(einstein_low, chapter=ch))
    save("p5_equalize", p05_histogram_eq.compute_equalization(einstein_low, chapter=ch))
    save("p5_transfer", p05_histogram_eq.compute_transfer_function(einstein_low, chapter=ch))
    save("p5_multi", p05_histogram_eq.compute_multi_equalize([
        {"chapter": ch, "filename": einstein_low},
        {"chapter": ch, "filename": cameraman},
        {"chapter": ch, "filename": skull},
        {"chapter": ch, "filename": galaxy},
    ]))

    # === Practical 6 ===
    einstein_high = next((i["filename"] for i in images if "einstein high" in i["filename"]), cameraman)
    print("Practical 6: Histogram Matching")
    save("p6_source_histogram", p06_histogram_matching.compute_source_histogram(einstein_low, chapter=ch))
    save("p6_equalize", p06_histogram_matching.compute_equalize_baseline(einstein_low, chapter=ch))
    save("p6_match", p06_histogram_matching.compute_matching(einstein_low, cameraman, src_chapter=ch, tgt_chapter=ch))
    save("p6_multi_target", p06_histogram_matching.compute_multi_target(einstein_low, [
        {"filename": einstein_high, "chapter": ch, "label": "High Contrast"},
        {"filename": cameraman, "chapter": ch, "label": "Cameraman"},
    ], src_chapter=ch))
    save("p6_transfer", p06_histogram_matching.compute_transfer_analysis(einstein_low, cameraman, src_chapter=ch, tgt_chapter=ch))

    # === Practical 7: Correlation & Convolution ===
    print("Practical 7: Correlation & Convolution")
    save("p7_impulse", p07_convolution.compute_impulse_demo())
    save("p7_filter", p07_convolution.compute_image_filtering(cameraman, chapter=ch))
    save("p7_verify", p07_convolution.compute_verify_cv2(cameraman, chapter=ch))

    # === Practical 8: Spatial Filtering ===
    # Needs CH03 (test pattern, salt-pepper, moon, contact lens). Pre-fetch it.
    print("Practical 8: Spatial Filtering")
    if ensure_chapter('CH03'):
        ch3_imgs = get_chapter_images('CH03')
        if ch3_imgs:
            save("p8_box", p08_filtering.compute_box_series(chapter='CH03'))
            save("p8_median", p08_filtering.compute_median_series(chapter='CH03'))
            save("p8_compare", p08_filtering.compute_box_vs_median(chapter='CH03'))
            save("p8_laplacian", p08_filtering.compute_laplacian(chapter='CH03'))
            save("p8_sobel", p08_filtering.compute_sobel(chapter='CH03'))
        else:
            print("  CH03 download failed; skipping P8 cache")
    else:
        print("  CH03 unavailable; skipping P8 cache")

    # === Image list (legacy) ===
    save("images", {"images": images, "count": len(images)})

    print(f"\nDone! {len(os.listdir(CACHE_DIR))} cache files in {CACHE_DIR}")


if __name__ == "__main__":
    main()