Delete core_pipeline.py

core_pipeline.py

@@ -1,40 +0,0 @@
-import cv2
-import os
-import tempfile
-import numpy as np
-from ultralytics import YOLO
-import matplotlib.pyplot as plt
-
-
-
-
-# Load YOLOv8 model (you can replace with your custom tree model)
-model = YOLO("./data/best.pt")  # Replace with tree-trained model
-
-
-def extract_frames(video_path, interval=30):
-    cap = cv2.VideoCapture(video_path)
-    frames = []
-    idx = 0
-    while True:
-        ret, frame = cap.read()
-        if not ret:
-            break
-        if idx % interval == 0:
-            frames.append(frame)
-        idx += 1
-    cap.release()
-    return frames
-
-def detect_trees(frame):
-    results = model(frame)
-    bboxes = results[0].boxes.xyxy.cpu().numpy()
-    confs = results[0].boxes.conf.cpu().numpy()
-    labels = results[0].boxes.cls.cpu().numpy()
-    return frame, bboxes, confs, labels
-
-def plot_detections(frame, bboxes):
-    for box in bboxes:
-        x1, y1, x2, y2 = box.astype(int)
-        cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
-    return frame