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seg5.py
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seg5.py
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import cv2
import os
import numpy as np
from segment_anything import sam_model_registry, SamPredictor
input_dir = 'input'
output_dir = 'output'
crop_mode=True#是否裁剪到最小范围
#alpha_channel是否保留透明通道
print('最好是每加一个点就按w键predict一次')
os.makedirs(output_dir, exist_ok=True)
image_files = [f for f in os.listdir(input_dir) if f.lower().endswith(('.png', '.jpg', '.jpeg','.JPG','.JPEG','.PNG'))]
sam = sam_model_registry["vit_b"](checkpoint="sam_vit_b_01ec64.pth")
_ = sam.to(device="cuda")#注释掉这一行，会用cpu运行，速度会慢很多
predictor = SamPredictor(sam)
def mouse_click(event, x, y, flags, param):
global input_point, input_label, input_stop
if not input_stop:
if event == cv2.EVENT_LBUTTONDOWN :
input_point.append([x, y])
input_label.append(1)
elif event == cv2.EVENT_RBUTTONDOWN :
input_point.append([x, y])
input_label.append(0)
else:
if event == cv2.EVENT_LBUTTONDOWN or event == cv2.EVENT_RBUTTONDOWN :
print('此时不能添加点,按w退出mask选择模式')
def apply_mask(image, mask, alpha_channel=True):
if alpha_channel:
alpha = np.zeros_like(image[..., 0])
alpha[mask == 1] = 255
image = cv2.merge((image[..., 0], image[..., 1], image[..., 2], alpha))
else:
image = np.where(mask[..., None] == 1, image, 0)
return image
def apply_color_mask(image, mask, color, color_dark = 0.5):
for c in range(3):
image[:, :, c] = np.where(mask == 1, image[:, :, c] * (1 - color_dark) + color_dark * color[c], image[:, :, c])
return image
def get_next_filename(base_path, filename):
name, ext = os.path.splitext(filename)
for i in range(1, 101):
new_name = f"{name}_{i}{ext}"
if not os.path.exists(os.path.join(base_path, new_name)):
return new_name
return None
def save_masked_image(image, mask, output_dir, filename, crop_mode_):
if crop_mode_:
y, x = np.where(mask)
y_min, y_max, x_min, x_max = y.min(), y.max(), x.min(), x.max()
cropped_mask = mask[y_min:y_max+1, x_min:x_max+1]
cropped_image = image[y_min:y_max+1, x_min:x_max+1]
masked_image = apply_mask(cropped_image, cropped_mask)
else:
masked_image = apply_mask(image, mask)
filename = filename[:filename.rfind('.')]+'.png'
new_filename = get_next_filename(output_dir, filename)
if new_filename:
if masked_image.shape[-1] == 4:
cv2.imwrite(os.path.join(output_dir, new_filename), masked_image, [cv2.IMWRITE_PNG_COMPRESSION, 9])
else:
cv2.imwrite(os.path.join(output_dir, new_filename), masked_image)
print(f"Saved as {new_filename}")
else:
print("Could not save the image. Too many variations exist.")
current_index = 0
cv2.namedWindow("image")
cv2.setMouseCallback("image", mouse_click)
input_point = []
input_label = []
input_stop=False
while True:
filename = image_files[current_index]
image_orign = cv2.imread(os.path.join(input_dir, filename))
image_crop = image_orign.copy()
image = cv2.cvtColor(image_orign.copy(), cv2.COLOR_BGR2RGB)
selected_mask = None
logit_input= None
while True:
#print(input_point)
input_stop=False
image_display = image_orign.copy()
display_info = f'{filename} | Press s to save | Press w to predict | Press d to next image | Press a to previous image | Press space to clear | Press q to remove last point '
cv2.putText(image_display, display_info, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2, cv2.LINE_AA)
for point, label in zip(input_point, input_label):
color = (0, 255, 0) if label == 1 else (0, 0, 255)
cv2.circle(image_display, tuple(point), 5, color, -1)
if selected_mask is not None :
color = tuple(np.random.randint(0, 256, 3).tolist())
selected_image = apply_color_mask(image_display,selected_mask, color)
cv2.imshow("image", image_display)
key = cv2.waitKey(1)
if key == ord(" "):
input_point = []
input_label = []
selected_mask = None
logit_input= None
elif key == ord("w"):
input_stop=True
if len(input_point) > 0 and len(input_label) > 0:
predictor.set_image(image)
input_point_np = np.array(input_point)
input_label_np = np.array(input_label)
masks, scores, logits= predictor.predict(
point_coords=input_point_np,
point_labels=input_label_np,
mask_input=logit_input[None, :, :] if logit_input is not None else None,
multimask_output=True,
)
mask_idx=0
num_masks = len(masks)
while(1):
color = tuple(np.random.randint(0, 256, 3).tolist())
image_select = image_orign.copy()
selected_mask=masks[mask_idx]
selected_image = apply_color_mask(image_select,selected_mask, color)
mask_info = f'Total: {num_masks} | Current: {mask_idx} | Score: {scores[mask_idx]:.2f} | Press w to confirm | Press d to next mask | Press a to previous mask | Press q to remove last point | Press s to save'
cv2.putText(selected_image, mask_info, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2, cv2.LINE_AA)
cv2.imshow("image", selected_image)
key=cv2.waitKey(10)
if key == ord('q') and len(input_point)>0:
input_point.pop(-1)
input_label.pop(-1)
elif key == ord('s'):
save_masked_image(image_crop, selected_mask, output_dir, filename, crop_mode_=crop_mode)
elif key == ord('a') :
if mask_idx>0:
mask_idx-=1
else:
mask_idx=num_masks-1
elif key == ord('d') :
if mask_idx<num_masks-1:
mask_idx+=1
else:
mask_idx=0
elif key == ord('w') :
break
elif key == ord(" "):
input_point = []
input_label = []
selected_mask = None
logit_input= None
break
logit_input=logits[mask_idx, :, :]
print('max score:',np.argmax(scores),' select:',mask_idx)
elif key == ord('a'):
current_index = max(0, current_index - 1)
input_point = []
input_label = []
break
elif key == ord('d'):
current_index = min(len(image_files) - 1, current_index + 1)
input_point = []
input_label = []
break
elif key == 27:
break
elif key == ord('q') and len(input_point)>0:
input_point.pop(-1)
input_label.pop(-1)
elif key == ord('s') and selected_mask is not None :
save_masked_image(image_crop, selected_mask, output_dir, filename, crop_mode_=crop_mode)
if key == 27:
break