A whoooole lotta 4.0.x fixes.

check_scipy.py

@@ -0,0 +1,170 @@
+#!/usr/bin/env python3
+"""
+Diagnostic script to check for scipy/numpy issues.
+Run this BEFORE starting the web app.
+
+Usage:
+    python check_scipy.py
+"""
+
+import sys
+print(f"Python version: {sys.version}")
+print()
+
+# Check numpy
+try:
+    import numpy as np
+    print(f"NumPy version: {np.__version__}")
+    print(f"NumPy config:")
+    np.show_config()
+except ImportError as e:
+    print(f"NumPy not installed: {e}")
+except Exception as e:
+    print(f"NumPy error: {e}")
+
+print()
+print("-" * 50)
+print()
+
+# Check scipy
+try:
+    import scipy
+    print(f"SciPy version: {scipy.__version__}")
+except ImportError as e:
+    print(f"SciPy not installed: {e}")
+
+print()
+
+# Check PIL
+try:
+    from PIL import Image
+    print(f"Pillow version: {Image.__version__}")
+except ImportError as e:
+    print(f"Pillow not installed: {e}")
+
+print()
+print("-" * 50)
+print()
+
+# Test scipy DCT directly
+print("Testing scipy DCT...")
+try:
+    from scipy.fftpack import dct, idct
+    import numpy as np
+    
+    # Create test array
+    test = np.random.rand(8, 8).astype(np.float64)
+    print(f"Input array shape: {test.shape}, dtype: {test.dtype}")
+    
+    # Test 1D DCT
+    row = test[0, :]
+    result = dct(row, norm='ortho')
+    print(f"1D DCT result shape: {result.shape}, dtype: {result.dtype}")
+    
+    # Test 2D DCT (the potentially problematic operation)
+    result2d = dct(dct(test.T, norm='ortho').T, norm='ortho')
+    print(f"2D DCT result shape: {result2d.shape}, dtype: {result2d.dtype}")
+    
+    # Test inverse
+    recovered = idct(idct(result2d.T, norm='ortho').T, norm='ortho')
+    error = np.max(np.abs(test - recovered))
+    print(f"Round-trip error: {error}")
+    
+    if error < 1e-10:
+        print("✓ scipy DCT working correctly")
+    else:
+        print("⚠ scipy DCT has precision issues")
+        
+except Exception as e:
+    print(f"✗ scipy DCT failed: {e}")
+    import traceback
+    traceback.print_exc()
+
+print()
+print("-" * 50)
+print()
+
+# Test with larger array (more like real image processing)
+print("Testing with larger arrays (512x512)...")
+try:
+    from scipy.fftpack import dct, idct
+    import numpy as np
+    import gc
+    
+    # Simulate processing many 8x8 blocks
+    large_array = np.random.rand(512, 512).astype(np.float64)
+    print(f"Large array shape: {large_array.shape}, size: {large_array.nbytes} bytes")
+    
+    count = 0
+    for y in range(0, 512, 8):
+        for x in range(0, 512, 8):
+            block = large_array[y:y+8, x:x+8].copy()
+            dct_block = dct(dct(block.T, norm='ortho').T, norm='ortho')
+            recovered = idct(idct(dct_block.T, norm='ortho').T, norm='ortho')
+            large_array[y:y+8, x:x+8] = recovered
+            count += 1
+    
+    print(f"Processed {count} blocks successfully")
+    
+    del large_array
+    gc.collect()
+    
+    print("✓ Large array processing completed")
+    
+except Exception as e:
+    print(f"✗ Large array processing failed: {e}")
+    import traceback
+    traceback.print_exc()
+
+print()
+print("-" * 50)
+print()
+
+# Test PIL with large image
+print("Testing PIL with large image...")
+try:
+    from PIL import Image
+    import io
+    
+    # Create a large test image
+    img = Image.new('RGB', (4000, 3000), color=(128, 128, 128))
+    
+    # Save to bytes
+    buffer = io.BytesIO()
+    img.save(buffer, format='PNG')
+    img_bytes = buffer.getvalue()
+    print(f"Test image size: {len(img_bytes)} bytes")
+    
+    # Re-open and process
+    buffer2 = io.BytesIO(img_bytes)
+    img2 = Image.open(buffer2)
+    print(f"Re-opened image: {img2.size}, mode: {img2.mode}")
+    
+    # Convert to numpy array
+    import numpy as np
+    arr = np.array(img2)
+    print(f"NumPy array: {arr.shape}, dtype: {arr.dtype}")
+    
+    # Clean up
+    img.close()
+    img2.close()
+    buffer.close()
+    buffer2.close()
+    del arr
+    gc.collect()
+    
+    print("✓ PIL large image test completed")
+    
+except Exception as e:
+    print(f"✗ PIL test failed: {e}")
+    import traceback
+    traceback.print_exc()
+
+print()
+print("=" * 50)
+print("Diagnostics complete")
+print()
+print("If no errors above but web app still crashes, try:")
+print("1. pip install --upgrade scipy numpy pillow")
+print("2. pip install scipy==1.11.4 numpy==1.26.4  # Known stable versions")
+print("3. Check if using conda vs pip (mixing can cause issues)")