Create app.py

app.py

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+from PIL import Image, ImageDraw
+import gradio as gr
+import torch
+from transformers import DetrImageProcessor, DetrForObjectDetection
+
+#モデルの読み込み
+processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50", revision="no_timm")
+model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50", revision="no_timm")
+
+def detect_objects(image):
+    # 画像をモデルに入力する形式に変換
+    inputs = processor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+
+    # 出力を処理し、信頼度が0.9以上の検出結果を取得
+    target_sizes = torch.tensor([image.size[::-1]])
+    results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0]
+
+    # 検出結果を画像に描画
+    draw = ImageDraw.Draw(image)
+    for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
+        box = [round(i, 2) for i in box.tolist()]
+        draw.rectangle(box, outline="red", width=3)
+        draw.text((box[0], box[1]), f"{model.config.id2label[label.item()]}: {round(score.item(), 3)}", fill="red")
+
+    return image
+
+demo = gr.Interface(
+    fn=detect_objects,
+    inputs=gr.Image(type="pil", label="Input Image"),
+    outputs=gr.Image(type="pil", label="Output Image with Detected Objects"),
+    title="Object Detection with DETR",
+    description="Upload an image to detect objects using the DETR model."
+)
+
+demo.launch()