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output formatting improvements

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This commit is contained in:
Alex Matulich
2025-05-16 17:22:22 -07:00
parent 71148d3ce5
commit 61990088e0
2 changed files with 42 additions and 32 deletions
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65
scripts/geotiff2scad.py
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@@ -1,6 +1,6 @@
# Utility to convert GeoTIFF data to OpenSCAD, JSON, or PNG grayscale formats.
# Written with a lot of back-and-forth collaboration with ChatGPT
# 14 May 2025
# Written with some back-and-forth collaboration with ChatGPT
# 16 May 2025
# Sources of Planetary/Moon GeoTIFF Data (information below may be out of date)
#
@@ -23,12 +23,17 @@
# Files may be large (100–500 MB)! Some are .IMG or .JP2 and must be converted to .tif using GDAL.
# Some planetary datasets use planetocentric or planetographic projections — still usable for 2D mapping.
# ----------------------------
# Required modules
# ----------------------------
# builtin modules that should always be available
import os
import sys
import argparse
import json
# Require necessary other modules
def require_module(name, alias=None, install_hint=None):
try:
module = __import__(name)
@@ -44,7 +49,6 @@ def require_module(name, alias=None, install_hint=None):
print(f"Try: pip install {name}")
sys.exit(1)
# Require necessary other modules
require_module('rasterio', install_hint='pip install rasterio')
require_module('numpy', alias='np', install_hint='pip install numpy')
require_module('PIL.Image', alias='Image', install_hint='pip install pillow')
@@ -54,6 +58,7 @@ from rasterio.enums import Resampling
# ----------------------------
# Command-line argument parsing
# ----------------------------
parser = argparse.ArgumentParser(
description="Convert a GeoTIFF elevation file to an OpenSCAD 2D array using nonlinear elevation scaling.",
epilog="""Examples:
@@ -81,9 +86,8 @@ if output_ext not in [".scad", ".json", ".png"]:
output_type = output_ext[1:] # Removes the dot, e.g., 'json', 'png', 'scad'
output_filename = args.output
# ----------------------------
# Parse resize dimensions
# ----------------------------
def parse_resize(resize_str, aspect):
if "x" in resize_str:
w, h = map(int, resize_str.lower().split("x"))
@@ -102,21 +106,18 @@ with rasterio.open(args.input_file) as src:
input_width = src.width
input_height = src.height
output_width, output_height = parse_resize(args.resize, input_width/input_height)
print(f"Reading data from {args.input_file} and resampling to {output_width}×{output_height}")
print(f"Reading data from {args.input_file} and resampling")
data = src.read(1, out_shape=(1, output_height, output_width), resampling=Resampling.bilinear)
print("Processing data")
# Replace nodata values
nodata = src.nodata
if nodata is not None:
data[data == nodata] = 0
data = np.nan_to_num(data, nan=0)
# ----------------------------
# Basic elevation stats
# ----------------------------
raw_min = np.min(data)
raw_max = np.max(data)
print(f"Elevations after resampling: min={raw_min}, max={raw_max}")
min_land_value = args.min_land_value # e.g. 0.04
land_mask = data > 0 # positive elevations
@@ -157,45 +158,55 @@ if np.any(sea_mask):
# Map sea to [ -min_land_value … more negative ]
scaled[sea_mask] = -((sea_data - min_sea) * scale_factor + min_land_value)
# -----------------------------------------------------------------
# ----------------------------
# Output
# ----------------------------
# Compact formatter for json (no unnecessary whitespace)
def format_json_array(data_array):
return json.dumps(data_array, separators=(',', ':'))
# Compact formatter for OpenSCAD (no unnecessary whitespace)
# Compact formatter for OpenSCAD (no unnecessary whitespace, no leading zero before decimal point)
def format_val(val):
# Omit leading 0 and trailing zeros
out = f"{val:.2f}".lstrip("0").rstrip("0").rstrip(".") if val >= 0 else f"-{abs(val):.2f}".lstrip("0").rstrip("0").rstrip(".")
if (len(out) == 0): return "0"
else: return out
print("Writing output file")
# Compact formatter for json (no unnecessary whitespace, but has leading zeros for json standards compliance)
def format_json_array(data_array):
return json.dumps(data_array, separators=(',', ':'))
print(f"Original resolution: {src.width}×{src.height}")
print(f"Output resolution: {output_width}×{output_height}")
print(f"Resampled elevation range: {raw_min} to {raw_max}")
scel_min = np.min(scaled)
scel_max = np.max(scaled)
if output_type=="png":
# Normalize to 0–255 for 8-bit grayscale
scaled = (scaled - scaled.min()) / (scaled.max() - scaled.min())
scel_min = np.min(scaled*255).astype(np.uint8)
scel_max = np.max(scaled*255).astype(np.uint8)
print(f"Scaled elevation range: {format_val(scel_min)} to {format_val(scel_max)}")
print(f"Writing output file {output_filename}")
if output_type=="json":
formatted_array = [
[format_val(val) for val in row] for row in scaled.tolist()
[round(val, 2) for val in row] for row in scaled.tolist()
]
with open(output_filename, "w") as f:
json.dump({args.varname: formatted_array}, f, separators=(",", ":"))
elif output_type=="png":
from PIL import Image
# Normalize to 0–255 for 8-bit grayscale
scaled_normalized = (scaled - scaled.min()) / (scaled.max() - scaled.min())
img_array = (scaled_normalized * 255).astype(np.uint8)
img_array = (scaled * 255).astype(np.uint8)
img = Image.fromarray(img_array, mode='L')
img.save(output_filename)
else: # output .scad
with open(output_filename, "w") as f:
f.write(f"// Auto-generated terrain data\n")
f.write(f"// Source file: {args.input_file}\n")
f.write(f"// Original resolution: {src.width}x{src.height}\n")
f.write(f"// Output resolution: {output_width}x{output_height}\n")
f.write(f"// Raw elevation range: {raw_min:.2f} to {raw_max:.2f} meters\n")
f.write(f"// Scaled value range: {np.min(scaled):.4f} to {np.max(scaled):.4f}\n")
f.write(f"// Original resolution: {src.width}×{src.height}\n")
f.write(f"// Output resolution: {output_width}×{output_height}\n")
f.write(f"// Resampled elevation range: {raw_min} to {raw_max} meters\n")
f.write(f"// Scaled elevation range: {scel_min} to {scel_max}\n")
f.write(f"{args.varname} = [\n")
for row in scaled:
line = "[" + ",".join(format_val(val) for val in row) + "],\n"
f.write(line)
f.write("];\n")
print(f"✅ Done: Output saved to {output_filename}")

9
scripts/img2scad.html
View File

@@ -317,7 +317,6 @@ Alpha channel is ignored. After processing the image as desired, you may save it
let rotation = 0;
let flipH = false;
let flipV = false;
let fileSuffix = "";
let origDim = { width:0, height:0 };
let uncropDim = { width:0, height:0 };
let cropDim = { width:0, height:0 };
@@ -510,7 +509,6 @@ Alpha channel is ignored. After processing the image as desired, you may save it
grayscaleCtx.restore();
grayscaleSizeText.textContent = `Output size: ${finalWidth}×${finalHeight}`;
fileSuffix = finalWidth.toString()+"x"+finalHeight.toString();
updateKbytes();
}
@@ -715,10 +713,11 @@ Alpha channel is ignored. After processing the image as desired, you may save it
const arrayContent = grayscaleMatrix.map(row => {
return " [" + row.map(val => useUnit ? parseFloat((val/255.0).toFixed(3)) : val).join(",") + "]";
}).join(",\n");
const openscadArray = (arrayName.value.length>0 ? arrayName.value : 'image_array')+" = [\n" + arrayContent + "\n];";
const introcomment = " = [ // " + cropDim.width + "×" + cropDim.height + "\n";
const dimSuffix = "_"+cropDim.width + "x" + cropDim.height
const openscadArray = (arrayName.value.length>0 ? arrayName.value : 'image_array') + introcomment + arrayContent + "\n];";
const blob = new Blob([openscadArray], { type: "text/plain" });
let suffix = fileSuffix.length>0 ? (arrayName.value.length>0 ? fileSuffix : "image"+fileSuffix) : "image";
let filename = arrayName.value.length>0 ? arrayName.value+'_'+suffix+'.scad' : suffix+'.scad';
let filename = (arrayName.value.length>0 ? arrayName.value : "image_array") + dimSuffix + '.scad';
if (window.showSaveFilePicker) {
saveWithFilePicker(blob, filename);
} else {