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Runtime error
Runtime error
| try: | |
| import detectron2 | |
| except: | |
| import os | |
| os.system('pip install git+https://github.com/facebookresearch/detectron2.git') | |
| import cv2 | |
| import torch | |
| from matplotlib.pyplot import axis | |
| import gradio as gr | |
| import requests | |
| import numpy as np | |
| from torch import nn | |
| import requests | |
| import torch | |
| 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 | |
| from detectron2.utils.visualizer import ColorMode | |
| model_path = "https://huggingface.co/asalhi85/Smartathon-Detectron2/resolve/9f4d573340b033e651d4937906f23850f9b6bc57/phase2_detectron_model.pth" | |
| cfg = get_cfg() | |
| cfg.merge_from_file("./faster_rcnn_X_101_32x8d_FPN_3x.yaml") | |
| cfg.MODEL.ROI_HEADS.NUM_CLASSES = 11 | |
| cfg.MODEL.WEIGHTS = model_path | |
| my_metadata = MetadataCatalog.get("dbmdz_coco_all") | |
| #my_metadata.thing_classes = ["GRAFFITI", "FADED_SIGNAGE","POTHOLES","GARBAGE","CONSTRUCTION_ROAD","BROKEN_SIGNAGE","BAD_STREETLIGHT","BAD_BILLBOARD","SAND_ON_ROAD","CLUTTER_SIDEWALK","UNKEPT_FACADE"] | |
| my_metadata.thing_classes = ["None", "BAD_BILLBOARD","BROKEN_SIGNAGE","CLUTTER_SIDEWALK","CONSTRUCTION_ROAD","FADED_SIGNAGE","GARBAGE","GRAFFITI","POTHOLES","SAND_ON_ROAD","UNKEPT_FACADE"] | |
| # #smart_dict={'GRAFFITI' : 0.0 , 'FADED_SIGNAGE': 1.0 , 'POTHOLES': 2.0, | |
| # 'GARBAGE' : 3.0 , 'CONSTRUCTION_ROAD': 4.0 , 'BROKEN_SIGNAGE': 5.0, | |
| # 'BAD_STREETLIGHT' : 6.0 , 'BAD_BILLBOARD': 7.0 , 'SAND_ON_ROAD':8.0, | |
| # 'CLUTTER_SIDEWALK' : 9.0 , 'UNKEPT_FACADE': 10.0} | |
| if not torch.cuda.is_available(): | |
| cfg.MODEL.DEVICE = "cpu" | |
| def inference(image_url, image, min_score): | |
| if image_url: | |
| r = requests.get(image_url) | |
| if r: | |
| im = np.frombuffer(r.content, dtype="uint8") | |
| im = cv2.imdecode(im, cv2.IMREAD_COLOR) | |
| else: | |
| im = cv2.imread(image) | |
| # Model expect BGR! | |
| #im = image[:,:,::-1] | |
| cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = min_score | |
| predictor = DefaultPredictor(cfg) | |
| outputs = predictor(im) | |
| v = Visualizer(im[:,:,::-1], my_metadata, scale=1.2, instance_mode=ColorMode.IMAGE ) | |
| out = v.draw_instance_predictions(outputs["instances"].to("cpu")) | |
| return out.get_image() | |
| title = "Smartathon Phase2 Demo - Baseer" | |
| description = "This demo introduces an interactive playground for our trained Detectron2 model." | |
| article = '<p>Detectron model is available from our repository <a href="https://github.com/asalhi/Smartathon-Baseer">here</a>.</p>' | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Textbox(label="Image URL", placeholder=""), | |
| gr.inputs.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image"), | |
| gr.Slider(minimum=0.0, maximum=1.0, value=0.5, label="Minimum score"), | |
| ], | |
| gr.outputs.Image(type="pil", label="Output"), | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=[]).launch() | |