MayBe

python/pokedex_rpi.py

-import cv2
-import numpy as np
 import json
 import argparse
 import os
-from hailo_platform.pyhailort import HailoRT
+import numpy as np
+from picamera2 import Picamera2
+from picamera2.devices.hailo import Hailo
+import cv2
 
 # --- Argparse ---
 parser = argparse.ArgumentParser(description="Pokémon Classifier Inference with Hailo-8")
@@ -14,11 +15,9 @@ args = parser.parse_args()
 if args.model == "1":
     hef_path = "../models/ResNet50/pokedex_ResNet50.hef"
     json_path = "../models/ResNet50/class_names.json"
-    input_shape = (224, 224)
 elif args.model == "2":
     hef_path = "../models/Xception/pokedex_Xception.hef"
     json_path = "../models/Xception/class_names.json"
-    input_shape = (256, 256)
 else:
     raise ValueError("Invalid model selection")
 
@@ -26,57 +25,37 @@ else:
 with open(json_path, "r") as f:
     class_names = json.load(f)
 
-# --- Setup device and network ---
-device = HailoRT.Device()
-hef = HailoRT.Hef(hef_path)
-network_group = device.create_hef_group(hef)
-
-input_info = network_group.get_input_vstream_infos()[0]
-output_info = network_group.get_output_vstream_infos()[0]
-
-# --- Open webcam and capture image ---
-cap = cv2.VideoCapture(0)
-if not cap.isOpened():
-    print("-- Unable to open webcam")
-    exit(1)
-
-print("-- Capturing image...")
-ret, frame = cap.read()
-cap.release()
-
-if not ret:
-    print("-- Failed to capture image")
-    exit(1)
-
-# --- Try to display the captured image ---
-try:
-    cv2.imshow("Captured Image", frame)
-    print("-- Press any key to continue...")
-    cv2.waitKey(0)
-    cv2.destroyAllWindows()
-except cv2.error as e:
-    print("-- GUI display failed, saving and showing with feh instead...")
-    output_path = "/tmp/captured.png"
-    cv2.imwrite(output_path, frame)
-    os.system(f"feh --fullscreen {output_path}")
-
-# --- Preprocess image ---
-image = cv2.resize(frame, input_shape)
-image = image.astype(np.float32)
-
-# Standard Hailo normalization
-image -= [123.68, 116.779, 103.939]
-
-# NHWC → NCHW
-image = np.transpose(image, (2, 0, 1))   # (H, W, C) → (C, H, W)
-image = np.expand_dims(image, axis=0)    # Add batch dimension → (1, C, H, W)
-
-# --- Inference ---
-with HailoRT.VirtualStreams(input_info, output_info, network_group) as (input_vstreams, output_vstreams):
-    input_vstreams[0].send(image)
-    output_data = output_vstreams[0].recv()
-
-# --- Postprocess ---
-predicted_idx = int(np.argmax(output_data))
-predicted_name = class_names[predicted_idx]
-print(f"-- Predicted Pokémon: {predicted_name}")
+# --- Run inference ---
+with Hailo(hef_path) as hailo:
+    # Get model input shape (e.g., 224x224x3 or 256x256x3)
+    model_h, model_w, _ = hailo.get_input_shape()
+
+    # Setup and start the camera
+    picam2 = Picamera2()
+    main = {'size': (model_w, model_h), 'format': 'RGB888'}
+    config = picam2.create_preview_configuration(main)
+    picam2.start(config)
+
+    print("-- Capturing image...")
+    frame = picam2.capture_array()
+
+    # Optionally display the captured image
+    try:
+        cv2.imshow("Captured Image", frame)
+        print("-- Press any key to continue...")
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+    except cv2.error:
+        print("-- GUI display failed, saving and showing with feh instead...")
+        output_path = "/tmp/captured.png"
+        cv2.imwrite(output_path, frame)
+        os.system(f"feh --fullscreen {output_path}")
+
+    # Run inference
+    print("-- Running inference...")
+    inference_results = hailo.run(frame)
+
+    # Postprocess: find predicted class
+    predicted_idx = int(np.argmax(inference_results))
+    predicted_name = class_names[predicted_idx]
+    print(f"-- Predicted Pokémon: {predicted_name}")