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| import sys | |
| import subprocess | |
| subprocess.check_call([sys.executable, '-m', 'pip', 'install','git+https://github.com/facebookresearch/detectron2.git']) | |
| import numpy as np | |
| import gradio as gr | |
| from Code import Inference | |
| import detectron2 | |
| # import some common detectron2 utilities | |
| from detectron2 import model_zoo | |
| from detectron2.engine import DefaultPredictor | |
| from detectron2.config import get_cfg | |
| from detectron2.utils.visualizer import Visualizer | |
| from detectron2.data import MetadataCatalog, DatasetCatalog | |
| import os | |
| os.environ['CUDA_VISIBLE_DEVICES'] = '-1' | |
| sys.path.append("Repositories/") | |
| from dlclive import DLCLive, Processor | |
| import os | |
| import cv2 | |
| def run_Inference(input_img): | |
| ###Detectron: | |
| cfg = get_cfg() | |
| # add project-specific config (e.g., TensorMask) here if you're not running a model in detectron2's core library | |
| cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml")) | |
| cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.7 # set threshold for this model | |
| # Find a model from detectron2's model zoo. You can use the https://dl.fbaipublicfiles... url as well | |
| cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml") | |
| cfg.MODEL.DEVICE='cpu' | |
| predictor = DefaultPredictor(cfg) | |
| ##DLC: | |
| dlc_proc = Processor() | |
| dlc_liveObj = DLCLive("./Weights/DLC_DLC_Segmented_resnet_50_iteration-0_shuffle-1/", processor=dlc_proc) | |
| OutImg = Inference.Inference(input_img,predictor,dlc_liveObj,ScaleBBox=1.2,Dilate=5,DLCThreshold=0.3) | |
| return OutImg | |
| ##Get sample images | |
| ImgList = [os.path.join("Samples",img) for img in os.listdir("Samples")] | |
| # for imgPath in [os.path.join("Samples",img) for img in os.listdir("Samples")]: | |
| # frame = cv2.imread(filename=imgPath) | |
| # ImgList.append(frame) | |
| demo = gr.Interface(run_Inference, | |
| gr.Image(), | |
| "image", | |
| examples=ImgList, | |
| title="PigeonEverywhere", | |
| description="Upload a photo of pigeons, and get 2D keypoint estimation.\n For more info on how this was done, see: https://arxiv.org/abs/2308.15316 ") | |
| demo.launch() |