Update flask/app.py

flask/app.py

@@ -6,8 +6,12 @@ import base64
 import json
 import cv2
 import numpy as np
+import gradio as gr
 from flask import Flask, request, jsonify
 from time import gmtime, strftime
+from fastapi import FastAPI, File, UploadFile
+from fastapi.responses import JSONResponse
+from typing import Dict
 
 from engine.header import *
 
@@ -17,9 +21,7 @@ root_path = os.path.dirname(dir_path)
 
 MATCH_THRESHOLD = 0.67
 
-app = Flask(__name__) 
-app.config['SITE'] = "http://0.0.0.0:8000/"
-app.config['DEBUG'] = False
+app = FastAPI()
 
 version = get_version().decode('utf-8')
 print_info('\t <Recognito Face Recognition> \t version {}'.format(version))
@@ -36,7 +38,6 @@ def activate_sdk():
     if online_key is None:
         print_warning("Recognition online license key not found!")
     else:
-        print_info(f"FR_LICENSE_KEY: {online_key}")
         ret = init_sdk(dict_path.encode('utf-8'), online_key.encode('utf-8'))
 
     if ret == 0:
@@ -86,48 +87,58 @@ def generate_response(result, similarity=None, face_bboxes=None, face_features=N
     data["data"]["image1"] = images[0]
     data["data"]["image2"] = images[1]
 
-    response = jsonify(data)
-    response.status_code = 200
-    response.headers["Content-Type"] = "application/json; charset=utf-8"
-    return response
-    
-@app.route('/api/compare_face', methods=['POST'])
-def compare_face_api():
-    try:
-        file1 = request.files['image1']
-        image_mat1 = cv2.imdecode(np.frombuffer(file1.read(), np.uint8), cv2.IMREAD_COLOR)
-    except:
-        response = generate_response("Failed to open image1")
-        return response
+    return JSONResponse(content=data, status_code=200)
+
+@app.get("/")
+def read_root():
+    return {"status": "API is running"}
 
+def read_image(file: UploadFile) -> np.ndarray:
+    # Read the image file and convert it to OpenCV format
+    image_bytes = file.file.read()
+    image_np = np.frombuffer(image_bytes, np.uint8)
+    image = cv2.imdecode(image_np, cv2.IMREAD_COLOR)
+    return image
+    
+@app.post("/api/compare_face")
+async def compare_face_api(
+    image1: UploadFile = File(...),
+    image2: UploadFile = File(...)
+) -> JSONResponse:
     try:
-        file2 = request.files['image2']
-        image_mat2 = cv2.imdecode(np.frombuffer(file2.read(), np.uint8), cv2.IMREAD_COLOR)
-    except:
-        response = generate_response("Failed to open image2")
-        return response        
+        image_mat1 = read_image(image1)
+        image_mat2 = read_image(image2)
 
+    except Exception as e:
+        response = generate_response("Failed to open image")
+        return response
+        
     result, score, face_bboxes, face_features = compare_face(image_mat1, image_mat2, MATCH_THRESHOLD)
     response = generate_response(result, score, face_bboxes, face_features)
     return response
 
-
-@app.route('/api/compare_face_base64', methods=['POST'])
-def coompare_face_base64_api():
-    content = request.get_json()
-    
+def decode_base64_image(base64_string: str) -> np.ndarray:
     try:
-        image_base64_1 = content['image1']
-        image_mat1 = cv2.imdecode(np.frombuffer(base64.b64decode(image_base64_1), dtype=np.uint8), cv2.IMREAD_COLOR)
-    except:
-        response = generate_response("Failed to open image1")
-        return response
-
+        image_data = base64.b64decode(base64_string)
+        image_np = np.frombuffer(image_data, np.uint8)
+        image = cv2.imdecode(image_np, cv2.IMREAD_COLOR)
+        if image is None:
+            raise ValueError("Decoded image is None")
+        return image
+    except Exception as e:
+        raise ValueError(f"Failed to decode base64 image: {str(e)}")
+        
+@app.post("/api/compare_face_base64")
+async def compare_face_base64_api(
+    image1: str,
+    image2: str
+) -> JSONResponse:
+    
     try:
-        image_base64_2 = content['image2']
-        image_mat2 = cv2.imdecode(np.frombuffer(base64.b64decode(image_base64_2), dtype=np.uint8), cv2.IMREAD_COLOR)
+        image_mat1 = decode_base64_image(image1)
+        image_mat2 = decode_base64_image(image2)
     except:
-        response = generate_response("Failed to open image2")
+        response = generate_response("Failed to open image")
         return response
 
     result, score, face_bboxes, face_features = compare_face(image_mat1, image_mat2, MATCH_THRESHOLD)
@@ -138,5 +149,16 @@ if __name__ == '__main__':
     ret = activate_sdk()
     if ret != 0:
         exit(-1)
-    port = int(os.environ.get("PORT", 8000))
-    app.run(host='0.0.0.0', port=port)
+
+    dummy_interface = gr.Interface(
+        fn=lambda x: "API ready.",
+        inputs=gr.Textbox(label="Info"),
+        outputs=gr.Textbox(label="Response"),
+        allow_flagging="never"  # 🚫 disables writing to `flagged/`
+    )
+    
+    gr_app = gr.mount_gradio_app(app, dummy_interface, path="/gradio")
+    
+    import uvicorn
+    uvicorn.run(gr_app, host="0.0.0.0", port=8000)
+