Merge pull request #15 from CellTrackingChallenge/viz_feature

Viz feature
#14

Author: TimoK93

README.md

@@ -52,6 +52,12 @@ cd py-ctcmetrics
 pip install .
 ```
 
+**Note**: If you want to use the visualization feature, you need to install OpenCV or by installing the optional dependencies:
+```bash
+pip install py-ctcmetrics[viz]
+```
+
+
 ---
 
 ## Usage

ctc_metrics/scripts/visualize.py

@@ -43,7 +43,7 @@ def visualize(
         start_frame: int = 0,
         framerate: int = 30,
         opacity: float = 0.5,
-):  # pylint: disable=too-many-arguments,too-complex
+):  # pylint: disable=too-many-arguments,too-complex,too-many-locals
     """
     Visualizes the tracking results.
 
@@ -111,8 +111,12 @@ def visualize(
         print(f"\rFrame {img_name} (of {len(images)})", end="")
 
         # Visualize the image
+        img = tiff.imread(img_path)
+        p1, p99 = np.percentile(img, (1, 99))
+        img = np.clip((img - p1) / max(p99 - p1, 1e-5) * 255, 0, 255).astype(np.uint8)
+        img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
         viz = create_colored_image(
-            cv2.imread(img_path),
+            img,
             tiff.imread(res_path),
             labels=show_labels,
             frame=start_frame,

setup.py

@@ -2,17 +2,19 @@
 
 setup(
     name="py-ctcmetrics",
-    version="1.1.0",
+    version="1.2.0",
     packages=find_packages(),
     install_requires=[
         "numpy",
-        "opencv-python",
         "scikit-learn",
         "scipy",
         "tifffile",
         "imagecodecs",
         "pandas"
     ],
+    extras_require={
+        "viz": ["opencv-python"],
+    },
     author="Timo Kaiser",
     author_email="kaiser@tnt.uni-hannover.de",
     description="Metrics for Cell Tracking Challenges",