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import numpy as np
import cv2
from PIL import Image
from collections import OrderedDict
import os
from pathlib import Path
def crop_image(ocvimg, bbox_list):
H, W = ocvimg.shape[:2]
res = OrderedDict()
for idx, (x0, y0, x1, y1) in enumerate(bbox_list):
# clamp to image bounds
x0 = max(0, min(W, int(x0)))
y0 = max(0, min(H, int(y0)))
x1 = max(0, min(W, int(x1)))
y1 = max(0, min(H, int(y1)))
# skip invalid/empty crops
if x1 <= x0 or y1 <= y0:
# print(f"Invalid bbox after clamp: {(x0,y0,x1,y1)}")
continue
crop_bgr = ocvimg[y0:y1, x0:x1]
crop_rgb = cv2.cvtColor(crop_bgr, cv2.COLOR_BGR2RGB)
res[idx] = Image.fromarray(crop_rgb)
return res
def draw_bboxes(ocvimg, bbox_list, color=(0, 255, 0), thickness=4, clamp=True):
img = ocvimg.copy()
H, W = img.shape[:2]
for bbox in bbox_list:
x0, y0, x1, y1 = [int(round(v)) for v in bbox]
if clamp:
x0 = max(0, min(W - 1, x0))
y0 = max(0, min(H - 1, y0))
x1 = max(0, min(W - 1, x1))
y1 = max(0, min(H - 1, y1))
# skip invalid boxes
if x1 <= x0 or y1 <= y0:
continue
cv2.rectangle(img, (x0, y0), (x1, y1), color, thickness)
return img
def save_image(img, save_path):
os.makedirs(os.path.dirname(save_path) or ".", exist_ok=True)
ok = cv2.imwrite(save_path, img)
if not ok:
raise IOError(f"cv2.imwrite failed for: {save_path}")
return save_path
def find_same_class(predict_res, score, visited, index, List_class, List_score, threshold):
target_class = List_class[index]
for i in range(len(score)):
if List_class[i] == target_class:
if score[i] > threshold:
predict_res[i]["score"] = score[i]
visited[i] = 1
predict_res[i]["category_id"] = 1
else:
# predict_res[i]["score"] = float(List_score[i])*float(score[i])
if List_score[index] > 0.8 and List_score[i] > 0.8:
predict_res[i]["score"] = float(score[i])
visited[i] = 1
predict_res[i]["category_id"] = 1
def open_image_follow_symlink(path: str):
p = Path(path)
real = p.resolve(strict=True)
if not real.is_file():
raise FileNotFoundError(f"Resolved path is not a file: {real}")
return Image.open(real) |