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app2.py

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+import cv2
+import numpy as np
+import gradio as gr
+from detectron2 import model_zoo
+from detectron2.config import get_cfg
+from detectron2.engine import DefaultPredictor
+from detectron2.utils.visualizer import Visualizer
+from detectron2.data import MetadataCatalog
+
+def initialize_model():
+    for d in ["train", "test"]:
+        #DatasetCatalog.register("Animals_" + d, lambda d=d: get_wheat_dicts("Animal_Detection/" + d))
+        MetadataCatalog.get("Animals_" + d).set(thing_classes=["fox","sheep"])
+
+    wheat_metadata = MetadataCatalog.get("Animals_train")  
+    cfg = get_cfg()
+    cfg.MODEL.DEVICE = "cpu"
+    cfg.DATALOADER.NUM_WORKERS = 0
+    cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-InstanceSegmentation/mask_rcnn_R_101_C4_3x.yaml")
+    cfg.SOLVER.IMS_PER_BATCH = 2
+    cfg.SOLVER.BASE_LR = 0.00025
+    cfg.SOLVER.STEPS = []
+    cfg.MODEL.ROI_HEADS.BATCH_SIZE_PER_IMAGE = 128
+    cfg.MODEL.ROI_HEADS.NUM_CLASSES = 2
+    cfg.MODEL.WEIGHTS = "output/model_final.pth"
+    cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.95
+    predictor = DefaultPredictor(cfg)
+    return predictor
+
+def process_image(predictor, img):
+    outputs = predictor(img)
+    wheat_metadata = MetadataCatalog.get("Animals_train")
+    v = Visualizer(img[:, :, ::-1],
+                   metadata=wheat_metadata, 
+                   scale=1.5, 
+                   instance_mode="segmentation")
+    out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
+    processed_img = cv2.cvtColor(out.get_image()[:, :, ::-1], cv2.COLOR_BGR2RGB)
+    return processed_img
+
+def main(img):
+    predictor = initialize_model()
+    processed_img = process_image(predictor, img)
+    return processed_img
+
+
+iface = gr.Interface(
+    fn=main,
+    inputs="image",
+    outputs="image",
+    title="Fox & Sheep Computer Vision detector",
+    cache_examples=False,input_size=(5000, 5000), output_size=(8000, 8000)
+)
+iface.launch()

requirements.txt

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+pyyaml==5.1
+torch==1.8.0
+torchvision==0.9.0
+git+https://github.com/facebookresearch/detectron2.git detectron2
+opencv-contrib-python-headless