:rocket: deploy model

README.md

@@ -1,4 +1,13 @@
 ---
+title: racoons_detector_P2
+emoji: 👀
+colorFrom: red
+colorTo: yellow
+sdk: gradio
+sdk_version: 3.18.0
+app_file: app.py
+pinned: false
 license: apache-2.0
-title: Racoons Detector P2
 ---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+import PIL
+import torch
+from fastai.vision.all import models
+from icevision.all import ClassMap, tfms
+
+
+class_map = ClassMap(["racoon"])
+state_dict = torch.load("fasterRCNNRaccoons.pth")
+model = models.torchvision.faster_rcnn.model(
+    backbone=models.torchvision.faster_rcnn.backbones.resnet50_fpn,
+    num_classes=len(class_map),
+)
+model.load_state_dict(state_dict)
+
+size = 384
+
+def predict(img_file):
+    img = PIL.Image.open(img_file)
+    infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size), tfms.A.Normalize()])
+    pred_dict = models.torchvision.faster_rcnn.end2end_detect(
+        img, infer_tfms, model.to("cpu"), class_map=class_map, detection_threshold=0.5
+    )
+    return pred_dict["img"]
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(128, 128)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    examples=["raccoon-27.jpg", "raccoon-20.jpg"],
+).launch(share=False)

fasterRCNNRaccoons.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:dc8b41388ba629802263fa4924d009fff5373b1f8fa972a550c6147663fd393d
+size 165730557

requirements.txt

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+fastai
+icevision[all] --install-option="--no-deps"