Update app.py

app.py

@@ -2,80 +2,19 @@
 Run a rest API exposing the yolov5s object detection model
 """
 
-import io
-import torch
-from flask import Flask, request
-from PIL import Image
-from waitress import serve
-import subprocess
-import argparse
-import os
+import gradio as gr
+import requests
 
-'''
-#subprocess.run(["export", "FLASK_APP","=","app.py"]) 
-app = Flask(__name__)
 
-DETECTION_URL = "/v1/detect"
-
-
-@app.route(DETECTION_URL,methods=["POST"])
-def predict():
-    
-    #model = torch.hub.load('ultralytics/yolov5', 'custom', path='best2.pt', force_reload=True)  # force_reload to recache
-    
-    if not request.method == "POST":
-        return
-
-    if request.files.get("image"):
-        image_file = request.files["image"]
-        image_bytes = image_file.read()
-
-        img = Image.open(io.BytesIO(image_bytes))
-
-        results = model(img, size=640)  # reduce size=320 for faster inference
-        results=results.pandas().xyxy[0].to_json(orient="records")
-        return f"{results}"
-
-
-if __name__ == "__main__":
-
-    #subprocess.run(["export","FLASK_ENV","=","development"])
-    app.run(host="0.0.0.0", port=7860)  # debug=True causes Restarting with stat
-    #serve(app, host="0.0.0.0", port=7860)
-   
-if __name__ == "__main__":
+def detect(inp):
+    filename=inp
+    bs64Data=gr.processing_utils.encode_file_to_base64(filename)
+    r = requests.post(url='https://hf.space/gradioiframe/Sa-m/Political-Party-Symbol-Detector-V1/+/api/predict/',
+                  json={"data": [bs64Data]})
     
-    model = torch.hub.load('ultralytics/yolov5', 'custom', path='best2.pt', force_reload=True)  # force_reload to recache
-    app.run(host="0.0.0.0", port=7860,debug =True)  # debug=True causes Restarting with stat    
-'''
-
-
-
-app = Flask(__name__)
-
-
-@app.route('/')
-def index():
-
-    '''return '<iframe frameBorder="0" height="100%" src="{}/?__dark-theme={}" width="100%"></iframe>'.format(
-    os.getenv('INACCEL_URL'),request.args.get('__dark-theme', 'false'))'''
-    model = torch.hub.load('ultralytics/yolov5', 'custom', path='best2.pt', force_reload=True)  # force_reload to recache
+    return r.json()
     
-    if request.files.get("image"):
-        image_file = request.files["image"]
-        image_bytes = image_file.read()
-
-        img = Image.open(io.BytesIO(image_bytes))
-
-        results = model(img, size=640)  # reduce size=320 for faster inference
-        results.imgs # array of original images (as np array) passed to model for inference
-        results.render()  # updates results.imgs with boxes and labels
-        for img in results.imgs:
-            buffered = BytesIO()
-            img_base64 = Image.fromarray(img)
-            img_base64.save(buffered, format="JPEG")
-    return base64.b64encode(buffered.getvalue()).decode('utf-8')  # base64 encoded image with results
-
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=7860)
+inp = gr.inputs.Image(type='file', label="Input Image")
+output=gr.outputs.JSON(label='Response')
+io=gr.Interface(fn=analysis, inputs=inp, outputs=output, title='Party Symbol Detector API',)
+io.launch(debug=True,share=False)