refactor: change response to image and detections

.gitignore

@@ -0,0 +1,220 @@
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+
+*.jpg
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+*.jpeg

app.py

@@ -1,10 +1,11 @@
 from fastapi import FastAPI, UploadFile, status
-from fastapi.responses import StreamingResponse, JSONResponse
+from fastapi.responses import JSONResponse
 from ultralytics import YOLO
 import cv2
 import numpy as np
-from io import BytesIO
 from fastapi.middleware.cors import CORSMiddleware
+import base64
+
 app = FastAPI()
 
 app.add_middleware(
@@ -28,6 +29,7 @@ async def inference(file: UploadFile):
     img = np.frombuffer(image_bytes, dtype=np.uint8)
     img = cv2.imdecode(img, cv2.IMREAD_COLOR)
     results = model.predict(source=img, conf=0.5)
+    detections = []
     for r in results: 
         boxes = r.boxes
     for box in boxes: 
@@ -38,10 +40,14 @@ async def inference(file: UploadFile):
 
         label = box.cls[0].item()  
         label_name = model.names[label]  
+        detections.append(label_name)
         (text_width, text_height), baseline = cv2.getTextSize(label_name, cv2.FONT_HERSHEY_SIMPLEX, 0.9, 2)
         cv2.rectangle(img, (x1, y1 - text_height - baseline - 5), (x1 + text_width, y1), (255, 0, 255), -1)
         cv2.putText(img, label_name, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 0), 2)
     
     resp_img_bytes = cv2.imencode('.jpg', img)[1].tobytes()
-    resp_filename = f"inferenced_{file.filename}" if file.filename else "inferenced_image.jpg"
-    return StreamingResponse(BytesIO(resp_img_bytes), media_type="image/jpg", headers={"Content-Disposition": f"attachment; filename={resp_filename}"})
+    img_base64 = base64.b64encode(resp_img_bytes).decode('utf-8')
+    return JSONResponse({
+        "image": img_base64,
+        "detections": detections
+    })

python_client.py

@@ -0,0 +1,23 @@
+import requests
+import base64
+from PIL import Image
+from io import BytesIO
+import matplotlib.pyplot as plt
+
+with open('glioma.jpg', 'rb') as f:
+    files = {'file': ('glioma.jpg', f, 'image/jpeg')}
+    response = requests.post('http://localhost:8000/inference', files=files)
+
+result = response.json()
+
+img_data = base64.b64decode(result['image'])
+img = Image.open(BytesIO(img_data))
+
+plt.figure(figsize=(10, 8))
+plt.imshow(img)
+plt.title(f"Detections: {', '.join(result['detections'])}")
+plt.axis('off')
+plt.show()
+
+img.save('result_with_detections.jpg')
+print(f"Detections found: {result['detections']}")