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import cv2
from matplotlib import pyplot as plt
import torch
import numpy as np
from transformers import CLIPSegProcessor, CLIPSegForImageSegmentation
from segmentation_mask_overlay import overlay_masks
from typing import List
import logging
class CLIPSEG:
def __init__(self,model_name = "CIDAS/clipseg-rd64-refined",threshould=0.60):
self.clip_processor = CLIPSegProcessor.from_pretrained(model_name)
self.clip_model = CLIPSegForImageSegmentation.from_pretrained(model_name)
self.threshould = threshould
self.clip_model.to('cpu')
@staticmethod
def create_rgb_mask(mask,color=None):
color = tuple(np.random.choice(range(0,256), size=3))
gray_3_channel = cv2.merge((mask, mask, mask))
gray_3_channel[mask==255] = color
return gray_3_channel.astype(np.uint8)
def get_segmentation_mask(self,image_path:str,object_prompts:List):
image = cv2.cvtColor(cv2.imread(image_path),cv2.COLOR_BGR2RGB)
logging.info("objects found out from the image :{}".format(object_prompts))
predicted_masks = []
inputs = self.clip_processor(
text=object_prompts,
images=[image] * len(object_prompts),
padding="max_length",
return_tensors="pt",
)
with torch.no_grad(): # Use 'torch.no_grad()' to disable gradient computation
outputs = self.clip_model(**inputs)
preds = outputs.logits.unsqueeze(1)
# detections = outputs.logits[0] # Assuming class index 0
for i in range(preds.shape[0]):
predicted_mask = torch.sigmoid(preds[i][0]).detach().cpu().numpy()
predicted_mask = np.where(predicted_mask>self.threshould, 255,0)
predicted_masks.append(predicted_mask)
resize_image = cv2.resize(image,(352,352))
mask_labels = [f"{prompt}_{i}" for i,prompt in enumerate(object_prompts)]
cmap = plt.cm.tab20(np.arange(len(mask_labels)))[..., :-1]
bool_masks = [predicted_mask.astype('bool') for predicted_mask in predicted_masks]
final_mask = overlay_masks(resize_image,np.stack(bool_masks,-1),labels=mask_labels,colors=cmap,alpha=0.5,beta=0.7)
try:
cv2.imwrite('final_mask.png',final_mask)
return 'Segmentation image created : final_mask.png'
except Exception as e:
logging.error("Error while saving the final mask :",e)
return "unable to create a mask image " |