🔨 [examples/detection] Add simpler examples

Author: ishandutta0098

examples/detection/basic_detection.py

@@ -1,60 +1,20 @@
-"""
-Basic example showing how to use a single face detector.
-"""
-
-import argparse
 import os
-import shutil
 
 import cv2
 
 from mukh.detection import FaceDetector
 
-# Set up argument parser
-parser = argparse.ArgumentParser(description="Face Detection Example")
-parser.add_argument(
-    "--detection_model",
-    type=str,
-    choices=["blazeface", "mediapipe", "ultralight"],
-    default="mediapipe",
-    help="Choose the face detection model to use.",
-)
-parser.add_argument(
-    "--clear_output",
-    type=bool,
-    default=True,
-    help="Clear the output folder before saving new images.",
+# Initialize detector
+detection_model = (
+    "blazeface"  # Available models: "blazeface", "mediapipe", "ultralight"
 )
-args = parser.parse_args()
-
-# Clear output folder if specified
-if args.clear_output and os.path.exists("output_images"):
-    shutil.rmtree("output_images")
-os.makedirs("output_images", exist_ok=True)
-
-# Create detector
-detector = FaceDetector.create(args.detection_model)
+detector = FaceDetector.create(detection_model)
 
-# To view available models
-# print(detector.list_available_models())
+# Detect faces
+image_path = "demo_images/1.jpg"
+faces, annotated_image = detector.detect_with_landmarks(image_path)
 
-# Process all images in the demo_images folder
-demo_images_folder = "demo_images"
-for image_name in os.listdir(demo_images_folder):
-    if image_name.endswith((".jpg", ".png")):
-        # Get image path
-        image_path = os.path.join(demo_images_folder, image_name)
-
-        # Detect faces
-        faces, annotated_image = detector.detect_with_landmarks(image_path)
-
-        # Save output
-        output_image_path = os.path.join(
-            "output_images", f"{args.detection_model}_output_{image_name}"
-        )
-        cv2.imwrite(output_image_path, annotated_image)
-
-        # Print results
-        print(f"Found {len(faces)} faces in {image_name}")
-        for face in faces:
-            print(f"Face confidence: {face.bbox.confidence:.2f}")
+# Save output
+os.makedirs("output_images", exist_ok=True)
+output_path = f"output_images/1.jpg"
+cv2.imwrite(output_path, annotated_image)

examples/detection/basic_detection_folder.py

@@ -0,0 +1,57 @@
+"""
+Basic example showing how to use a single face detector.
+"""
+
+import argparse
+import os
+import shutil
+
+import cv2
+
+from mukh.detection import FaceDetector
+
+# Set up argument parser
+parser = argparse.ArgumentParser(description="Face Detection Example")
+parser.add_argument(
+    "--detection_model",
+    type=str,
+    choices=["blazeface", "mediapipe", "ultralight"],
+    default="mediapipe",
+    help="Choose the face detection model to use.",
+)
+parser.add_argument(
+    "--clear_output",
+    type=bool,
+    default=False,
+    help="Clear the output folder before saving new images.",
+)
+args = parser.parse_args()
+
+# Clear output folder if specified
+if args.clear_output and os.path.exists("output_images"):
+    shutil.rmtree("output_images")
+os.makedirs("output_images", exist_ok=True)
+
+# Create detector
+detector = FaceDetector.create(args.detection_model)
+
+# Process all images in the demo_images folder
+demo_images_folder = "demo_images"
+for image_name in os.listdir(demo_images_folder):
+    if image_name.endswith((".jpg", ".png")):
+        # Get image path
+        image_path = os.path.join(demo_images_folder, image_name)
+
+        # Detect faces
+        faces, annotated_image = detector.detect_with_landmarks(image_path)
+
+        # Save output
+        output_image_path = os.path.join(
+            "output_images", f"{args.detection_model}_output_{image_name}"
+        )
+        cv2.imwrite(output_image_path, annotated_image)
+
+        # Print results
+        print(f"Found {len(faces)} faces in {image_name}")
+        for face in faces:
+            print(f"Face confidence: {face.bbox.confidence:.2f}")