feat(visualizer): integrate image upload with similarity search

mini-nav/tests/test_visualizer.py

@@ -1,97 +1,35 @@
-"""Tests for FeatureVisualizer module."""
+"""Tests for visualizer app image upload similarity search."""
 
-import os
-import tempfile
+import base64
+import io
 
 import numpy as np
-import pytest
-import torch
-from feature_compressor.core.visualizer import FeatureVisualizer
+from PIL import Image
 
 
-class TestFeatureVisualizer:
-    """Test suite for FeatureVisualizer class."""
+class TestImageUploadSimilaritySearch:
+    """Test suite for image upload similarity search functionality."""
 
-    def test_histogram_generation(self):
-        """Test histogram generation from features."""
+    def test_base64_to_pil_image(self):
+        """Test conversion from base64 string to PIL Image."""
+        # Create a test image
+        img_array = np.random.randint(0, 255, (224, 224, 3), dtype=np.uint8)
+        img = Image.fromarray(img_array)
 
-        viz = FeatureVisualizer()
-        features = torch.randn(20, 256)
+        # Convert to base64
+        buffer = io.BytesIO()
+        img.save(buffer, format="PNG")
+        img_base64 = base64.b64encode(buffer.getvalue()).decode("utf-8")
 
-        fig = viz.plot_histogram(features, title="Test Histogram")
+        # Add data URI prefix (as Dash provides)
+        img_base64_with_prefix = f"data:image/png;base64,{img_base64}"
 
-        assert fig is not None
-        assert "Test Histogram" in fig.layout.title.text
+        # Parse base64 to PIL Image
+        # Remove prefix
+        base64_str = img_base64_with_prefix.split(",")[1]
+        img_bytes = base64.b64decode(base64_str)
+        parsed_img = Image.open(io.BytesIO(img_bytes))
 
-    def test_pca_2d_generation(self):
-        """Test PCA 2D scatter plot generation."""
-
-        viz = FeatureVisualizer()
-        features = torch.randn(20, 256)
-        labels = ["cat"] * 10 + ["dog"] * 10
-
-        fig = viz.plot_pca_2d(features, labels=labels)
-
-        assert fig is not None
-        assert "PCA 2D" in fig.layout.title.text
-
-    def test_comparison_plot_generation(self):
-        """Test comparison plot generation."""
-
-        viz = FeatureVisualizer()
-        features_list = [torch.randn(20, 256), torch.randn(20, 256)]
-        names = ["Set A", "Set B"]
-
-        fig = viz.plot_comparison(features_list, names)
-
-        assert fig is not None
-        assert "Comparison" in fig.layout.title.text
-
-    def test_html_export(self):
-        """Test HTML export format."""
-
-        viz = FeatureVisualizer()
-        features = torch.randn(10, 256)
-
-        fig = viz.plot_histogram(features)
-
-        with tempfile.TemporaryDirectory() as tmpdir:
-            output_path = os.path.join(tmpdir, "test_plot")
-            viz.save(fig, output_path, formats=["html"])
-
-            assert os.path.exists(output_path + ".html")
-
-    def test_png_export(self):
-        """Test PNG export format."""
-
-        viz = FeatureVisualizer()
-        features = torch.randn(10, 256)
-
-        fig = viz.plot_histogram(features)
-
-        with tempfile.TemporaryDirectory() as tmpdir:
-            output_path = os.path.join(tmpdir, "test_plot")
-
-            # Skip PNG export if Chrome not available
-            try:
-                viz.save(fig, output_path, formats=["png"])
-                assert os.path.exists(output_path + ".png")
-            except RuntimeError as e:
-                if "Chrome" in str(e):
-                    pass
-                else:
-                    raise
-
-    def test_json_export(self):
-        """Test JSON export format."""
-
-        viz = FeatureVisualizer()
-        features = torch.randn(10, 256)
-
-        fig = viz.plot_histogram(features)
-
-        with tempfile.TemporaryDirectory() as tmpdir:
-            output_path = os.path.join(tmpdir, "test_plot")
-            viz.save(fig, output_path, formats=["json"])
-
-            assert os.path.exists(output_path + ".json")
+        # Verify the image is valid
+        assert parsed_img.size == (224, 224)
+        assert parsed_img.mode == "RGB"