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Suppression de la visualisation Texture GLCM

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- Suppression de generate_texture() de visualizations.py
- Suppression de l'entrée 'texture' de VIZ_STEPS et COLORMAPS
- Suppression du test TestTexture
- Mise à jour README (19 → 18 visualisations)
- Mise à jour CLAUDE.md (17 → 16 fonctions generate_*)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Jacquin Antoine
2026-05-10 03:30:07 +02:00
parent bc92689acc
commit f03b3873bd
6 changed files with 8 additions and 107 deletions
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3
lidar_pipeline/pipeline.py
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@ -44,7 +44,7 @@ from .visualizations import (
generate_hillshade, generate_slope, generate_aspect, generate_curvature,
generate_lrm, generate_svf, generate_openness,
generate_mslrm, generate_tpi, generate_depressions, generate_sailore,
generate_roughness, generate_anomalies, generate_wavelet, generate_texture,
generate_roughness, generate_anomalies, generate_wavelet,
generate_flow,
)
from .gpu import gpu_cleanup
@ -71,7 +71,6 @@ VIZ_STEPS = [
('roughness', generate_roughness),
('anomalies', generate_anomalies),
('wavelet', generate_wavelet),
('texture', generate_texture),
('flow', generate_flow),
('ortho', lambda d, b, v, r: generate_ign_overlay(
d, b, v, r,

9
lidar_pipeline/rendering.py
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@ -156,13 +156,6 @@ COLORMAPS = {
'description': 'Transformée en ondelette 2D — excellente pour détecter structures circulaires',
'vmin_mode': 'symmetric', 'sym_pct': (2, 98),
},
'texture': {
'cmap': 'inferno',
'title': 'Texture GLCM (Contraste + Entropie - Homogénéité)',
'legend': 'Analyse de la texture du relief (fenêtre 5m)\nClair = Texture hétérogène (labour, ruines, sol perturbé)\nSombre = Texture homogène (sol nu, route, zone plate)\n\nCombine contraste, entropie et homogénéité',
'description': 'Distingue surfaces anthropiques (labour, chemins) des naturelles',
'vmin_mode': 'symmetric', 'sym_pct': (2, 98),
},
'flow': {
'cmap': 'Blues',
'title': 'Accumulation de Flux Hydrologique (D8)',
@ -525,7 +518,7 @@ def generate_pdf_report(basename, vis_dir, pdf_dir, resolution):
order = ['mslrm', 'svf', 'negative_openness',
'positive_openness', 'sailore', 'depressions', 'hillshade_multi',
'lrm', 'tpi', 'slope', 'curvature', 'aspect',
'roughness', 'anomalies', 'wavelet', 'texture', 'flow']
'roughness', 'anomalies', 'wavelet', 'flow']
def sort_key(f):
name = f.stem.lower()

8
lidar_pipeline/tests/test_visualizations.py
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@ -190,14 +190,6 @@ class TestWavelet:
assert result.exists()
class TestTexture:
def test_generates_tif(self, synthetic_dem, tmp_output_dir):
from lidar_pipeline.visualizations import generate_texture
result = generate_texture(synthetic_dem, "test", tmp_output_dir, 5.0)
assert result is not None
assert result.exists()
class TestFlow:
def test_generates_tif(self, synthetic_dem, tmp_output_dir):
from lidar_pipeline.visualizations import generate_flow

82
lidar_pipeline/visualizations.py
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@ -676,88 +676,6 @@ def generate_wavelet(dem_file, basename, vis_dir, resolution):
return None
# ============================================================
# Texture GLCM
# ============================================================
def generate_texture(dem_file, basename, vis_dir, resolution):
"""GLCM-inspired texture analysis — contrast, entropy, homogeneity (GPU-accelerated)."""
gpu_tag = " [GPU]" if HAS_GPU else ""
logger.info(f" → Texture GLCM{gpu_tag}...")
t0 = time.time()
output = vis_dir / f"{basename}_texture.tif"
try:
dem_np, transform, crs = _read_dem(dem_file)
# Hillshade — compute on CPU to avoid holding DEM on GPU during texture
gy, gx = np.gradient(dem_np, resolution)
slope = np.arctan(np.sqrt(gx**2 + gy**2))
alt_rad = np.radians(45)
az_rad = np.radians(315)
aspect = np.arctan2(gy, gx)
shading = (np.sin(alt_rad) * np.cos(slope) +
np.cos(alt_rad) * np.sin(slope) *
np.cos(az_rad - aspect))
hillshade = np.clip(shading, 0, 1)
valid = np.asarray(hillshade[~np.isnan(hillshade)])
if len(valid) == 0:
raise ValueError("No valid data for texture analysis")
lo, hi = np.percentile(valid, (1, 99))
img = np.clip((hillshade - lo) / max(hi - lo, 0.001), 0, 1)
del hillshade, shading, slope, aspect, gy, gx # free memory
window = int(5 / resolution)
if window % 2 == 0:
window += 1
# Contrast (variance) — GPU-accelerated
img_gpu = to_gpu(img.astype(np.float32))
local_mean = xp_uniform_filter(img_gpu, size=window)
local_mean_sq = xp_uniform_filter(img_gpu * img_gpu, size=window)
contrast = to_cpu(local_mean_sq - local_mean * local_mean).astype(np.float64)
del img_gpu, local_mean, local_mean_sq # free GPU memory
# Entropy — compute bin-by-bin to avoid large 3D allocation
n_bins = 16
img_clean = np.nan_to_num(img, nan=0.0)
img_uint8 = np.clip(img_clean * 255, 0, 255).astype(np.uint8)
quantized = (img_uint8 // (256 // n_bins)).astype(np.int32)
entropy = np.zeros_like(img, dtype=np.float64)
win_area = max(window * window, 1)
for b in range(n_bins):
plane = (quantized == b).astype(np.float32)
plane_gpu = to_gpu(plane)
prob_plane = to_cpu(xp_uniform_filter(plane_gpu, size=window))
prob_val = prob_plane / win_area
prob_val = np.clip(prob_val, 1e-10, None)
entropy -= prob_val * np.log2(prob_val)
del plane_gpu # free GPU memory per bin
del quantized, img_uint8 # free CPU memory
# Homogeneity — 1 / (1 + variance)
homogeneity = 1.0 / (1.0 + contrast)
def norm(arr):
valid_arr = arr[~np.isnan(arr)]
if len(valid_arr) == 0:
return arr
std_val = max(np.std(valid_arr), 0.01)
return (arr - np.mean(valid_arr)) / std_val
texture_combined = 0.4 * norm(contrast) + 0.4 * norm(entropy) - 0.2 * norm(homogeneity)
_save_tif(output, texture_combined, transform, crs)
logger.info(f" ✓ Texture terminée ({time.time()-t0:.1f}s){gpu_tag}")
return output
except Exception as e:
logger.error(f" ✗ Erreur texture GLCM: {e}", exc_info=True)
return None
# ============================================================
# Flow accumulation
# ============================================================