rpotter6298
72 lines
2.9 KiB
Python
72 lines
2.9 KiB
Python
#!/usr/bin/env python3
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"""figure1.py — Sample CT images from the IQ-OTH/NCCD dataset, one per patient.
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Usage: python scripts/visualizations/figure1.py [--tag TAG]"""
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import os, sys, csv, argparse
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import matplotlib; matplotlib.use("Agg")
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import matplotlib.pyplot as plt
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from PIL import Image
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(
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os.path.abspath(__file__)))))
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ROOT = os.path.dirname(os.path.dirname(os.path.dirname(
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os.path.abspath(__file__))))
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DATASET = os.path.join(os.path.dirname(ROOT), "The IQ-OTHNCCD lung cancer dataset")
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MANIFEST = os.path.join(ROOT, "results", "simple_patient_manifest.csv")
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PLOTS_DIR = os.path.join(ROOT, "plots")
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ap = argparse.ArgumentParser()
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ap.add_argument("--tag", default="", help="Append tag to filename")
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ap.add_argument("--manifest", default=MANIFEST, help="Patient manifest CSV")
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args = ap.parse_args()
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tag = f"_{args.tag}" if args.tag else ""
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# Load manifest to get per-patient images
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patients = {"Benign": [], "Malignant": [], "Normal": []}
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with open(args.manifest, newline="") as f:
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reader = csv.DictReader(f)
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img_col = "confirmed_images" if "confirmed_images" in reader.fieldnames else "images"
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for row in reader:
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cls = row.get("class", "")
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if cls in patients:
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imgs = row[img_col].split(";")
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if imgs:
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patients[cls].append((row["patient_id"], imgs[0])) # first image per patient
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CLASS_DIR = {"Benign": "Bengin cases", "Malignant": "Malignant cases",
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"Normal": "Normal cases"}
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N_EXAMPLES = 3
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fig, axes = plt.subplots(3, N_EXAMPLES, figsize=(8, 9))
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for row, (cls_label, cls_dir) in enumerate(CLASS_DIR.items()):
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# Pick first N_EXAMPLES patients for this class
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selected = patients[cls_label][:N_EXAMPLES]
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for col, (pid, short_name) in enumerate(selected):
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ax = axes[row, col]
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# Convert short name back to original filename
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prefix = short_name[0]
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num = int(short_name.split("_")[1])
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cls_map = {"B": ("Bengin cases", "Bengin"), "M": ("Malignant cases", "Malignant"),
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"N": ("Normal cases", "Normal")}
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dir_name, file_prefix = cls_map[prefix]
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fname = f"{file_prefix} case ({num}).jpg"
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img_path = os.path.join(DATASET, dir_name, fname)
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try:
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img = Image.open(img_path).convert("L")
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ax.imshow(img, cmap="gray")
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except Exception as e:
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ax.text(0.5, 0.5, f"error: {e}", ha="center", va="center", fontsize=7)
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ax.set_xticks([]); ax.set_yticks([])
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if col == 0:
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ax.set_ylabel(cls_label, fontsize=10, rotation=0,
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labelpad=20, va="center")
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fig.suptitle("Figure 1 — Sample images from the IQ-OTH/NCCD dataset",
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fontsize=12, y=1.02)
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plt.tight_layout(rect=[0, 0, 1, 0.97])
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out = os.path.join(PLOTS_DIR, "figure1", f"figure1{tag}.png")
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os.makedirs(os.path.dirname(out), exist_ok=True)
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plt.savefig(out, dpi=150)
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plt.close()
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print(f"Saved → {out}")
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