Upload 7 files

app.py

@@ -0,0 +1,80 @@
+import gradio as gr
+import requests
+import torch
+import torch.nn as nn
+from PIL import Image
+from torchvision.models import resnet18
+from torchvision.transforms import functional as F
+
+def main():
+    # title
+    title = 'Cucumber Diseases Diagnosis'
+    # description
+    description = """ このデモは、きゅうりの葉の病害を分類することを目的としたプロジェクトの進行中のアプリケーションである。
+    現在、健全含む病害10種を分類することができます。 
+    このモデルはこちらでご覧になれます：https://huggingface.co/spaces/celery22/cucumber_diseases_diagnosis
+    お楽しみください。
+    """
+    # model_path
+    model_path = 'cucumber_resnet18_last_model.pth'
+    # class_name
+    class_name = ["健全","うどんこ病","灰色かび病","炭疽病","べと病","褐斑病","つる枯病","斑点細菌病","CCYV","モザイク病","MYSV"]
+    
+    # example
+    example=[
+            ['image/231305_20200302150233_01.JPG'],
+            ['image/0004_20181120084837_01.jpg'],
+            ['image/160001_20170830173740_01.JPG'],
+            ['image/152300_20190119175054_01.JPG'],
+            
+        ]
+
+    # model定義
+    model_ft = resnet18(num_classes = len(class_name),pretrained=False)
+    device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+    model_ft = model_ft.to(device)
+    if torch.cuda.is_available():
+        model_ft.load_state_dict(torch.load(model_path))
+    else:
+        model_ft.load_state_dict(
+            torch.load(model_path, map_location=torch.device("cpu"))
+        )
+    model_ft.eval()
+
+    # 画像分類を行う関数を定義
+    @torch.no_grad()
+    def inference(gr_input):
+        img = Image.fromarray(gr_input.astype("uint8"), "RGB")
+
+        # 前処理
+        img = F.resize(img, (224, 224))
+        img = F.to_tensor(img)
+        img = img.unsqueeze(0)
+
+        # 推論
+        output = model_ft(img).squeeze(0)
+        probs = nn.functional.softmax(output, dim=0).numpy()
+        labels_lenght =len(class_name)
+        # ラベルごとの確率をdictとして返す
+        return {class_name[i]: float(probs[i]) for i in range(labels_lenght)}
+    
+    
+    # 入力の形式を画像とする
+    inputs = gr.inputs.Image()
+
+    # 出力はラベル形式で，top5まで表示する
+    outputs = gr.outputs.Label(num_top_classes=5)
+
+    # サーバーの立ち上げ
+    interface = gr.Interface(fn=inference, 
+        inputs=[inputs], 
+        outputs=outputs,
+        examples=example,
+        title=title,
+        description=description)
+
+    interface.launch()
+
+
+if __name__ == "__main__":
+    main()

cucumber_resnet18_last_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46ea5b3332a072a019bc4f78fb86e172ad39f3e38b463cb194170501f903eba1
+size 44806605

requirements.txt

@@ -0,0 +1,74 @@
+aiofiles==22.1.0
+aiohttp==3.8.3
+aiosignal==1.3.1
+altair==4.2.0
+anyio==3.6.2
+asgiref==3.6.0
+async-timeout==4.0.2
+attrs==22.2.0
+backports.zoneinfo==0.2.1
+certifi==2022.12.7
+charset-normalizer==2.1.1
+click==8.1.3
+contourpy==1.0.7
+cycler==0.11.0
+dj-database-url==1.2.0
+Django==4.1.4
+django-environ==0.9.0
+entrypoints==0.4
+fastapi==0.89.1
+ffmpy==0.3.0
+fonttools==4.38.0
+frozenlist==1.3.3
+fsspec==2022.11.0
+gradio==3.16.2
+h11==0.14.0
+httpcore==0.16.3
+httpx==0.23.3
+idna==3.4
+importlib-resources==5.10.2
+Jinja2==3.1.2
+jsonschema==4.17.3
+kiwisolver==1.4.4
+linkify-it-py==1.0.3
+markdown-it-py==2.1.0
+MarkupSafe==2.1.1
+matplotlib==3.6.3
+mdit-py-plugins==0.3.3
+mdurl==0.1.2
+multidict==6.0.4
+numpy==1.24.0
+opencv-python==4.6.0.66
+orjson==3.8.5
+packaging==23.0
+pandas==1.5.2
+Pillow==9.3.0
+pkgutil_resolve_name==1.3.10
+psycopg2==2.9.5
+pycryptodome==3.16.0
+pydantic==1.10.4
+pydub==0.25.1
+pyparsing==3.0.9
+pyrsistent==0.19.3
+python-dateutil==2.8.2
+python-decouple==3.7
+python-multipart==0.0.5
+pytz==2022.7.1
+PyYAML==6.0
+requests==2.28.1
+rfc3986==1.5.0
+six==1.16.0
+sniffio==1.3.0
+sqlparse==0.4.3
+starlette==0.22.0
+toolz==0.12.0
+torch==1.13.1
+torchvision==0.14.1
+typing_extensions==4.4.0
+uc-micro-py==1.0.1
+urllib3==1.26.13
+uvicorn==0.20.0
+websockets==10.4
+whitenoise==6.3.0
+yarl==1.8.2
+zipp==3.11.0