carte continue: cropped images + continuous map + PDF download via jsPDF

lidar_pipeline/rendering.py

@@ -780,6 +780,70 @@ def tif_to_png(tif_file, vis_dir, resolution, keep_tif=False, source_info=None,
         return None
 
 
+def tif_to_crop(tif_file, vis_dir, resolution, keep_tif=False, quality=98, output_format='avif'):
+    """Convert GeoTIFF to a cropped visualization image (no legend, no overlay).
+
+    Applies colormap and saves the image as a pure 1×1 km square.
+    Used for grid/map display where images must tile seamlessly.
+
+    Args:
+        tif_file: Path to input GeoTIFF.
+        vis_dir: Output directory for the image file.
+        resolution: Grid resolution in m/px.
+        keep_tif: If True, keep the source TIFF after conversion.
+        quality: Image quality (1-100). Use 100 for lossless.
+        output_format: Output format ('webp' or 'avif').
+
+    Returns:
+        Path to output image file, or None on failure.
+    """
+    if not tif_file or not tif_file.exists():
+        return None
+
+    ext = 'avif' if output_format == 'avif' else 'webp'
+    output_file = vis_dir / f"{tif_file.stem}.{ext}"
+
+    try:
+        with rasterio.open(tif_file) as src:
+            is_rgb = src.count >= 3 and any(k in str(tif_file) for k in ('ortho', 'topo'))
+
+            if is_rgb:
+                data = src.read([1, 2, 3])
+                data = np.moveaxis(data, 0, -1)
+            else:
+                data = src.read(1)
+
+        # Apply colormap normalization
+        data, cmap_name, title, legend_label, description, is_rgb_result = _apply_colormap(data, tif_file)
+
+        # Convert to RGB using colormap
+        if is_rgb_result:
+            # RGB images are already in RGB
+            rgb_data = (data * 255).astype(np.uint8)
+        else:
+            # Normalize data to 0-1 range for colormap
+            cmap = plt.get_cmap(cmap_name)
+            rgb_float = cmap(data.clip(0, 1))
+            rgb_data = (rgb_float[:, :, :3] * 255).astype(np.uint8)
+
+        # Save as AVIF/WebP
+        img = PILImage.fromarray(rgb_data)
+        pil_format = 'AVIF' if output_format == 'avif' else 'WEBP'
+        if quality >= 100:
+            img.save(str(output_file), format=pil_format, lossless=True)
+        else:
+            img.save(str(output_file), format=pil_format, quality=quality)
+
+        # Delete source TIFF (unless --keep-tif)
+        if not keep_tif:
+            tif_file.unlink(missing_ok=True)
+
+        return output_file
+
+    except Exception as e:
+        logger.error(f"    Erreur conversion crop {ext.upper()}: {e}", exc_info=True)
+        return None
+
 
 def generate_pdf_report(basename, vis_dir, pdf_dir, resolution):
     """Generate A3 PDF report for a LiDAR file with all visualizations.