Added readme + enhances

README.md

@@ -1,12 +1,40 @@
+# El7a2ny Backend
+
+A mobile application built using Flutter. This README provides clear instructions for both developers and non-developers to run or test the app.
+
 ---
-title: Deploy El7a2ny Application
-emoji: ⚡
-colorFrom: gray
-colorTo: indigo
-sdk: docker
-pinned: false
-license: apache-2.0
-short_description: El7a2ny App
+
+## El7a2ny Overview
+
+El7a2ny is an emergency mobile app that tackeles real-life emergency situations and help its users tackle them in a user-friendly way.
+
+The app includes 3 main features:
+
+ - ECG Analysis, export your apple smart watch ECG PDF analysis, import it into our mobile, do a checkup and diagnose your ECG analysis to ensure it is normal or has a kind of abnormalities, and will guide you to the correct procedures accordingly.
+
+ - Skin burns, got a burn at your home from a stove or boiling water? take a picture and upload it to the app, we will segment the burn, and classify the degree and prompt you with the correct guidlines accordingly.
+
+ - CPR analysis, with our educational CPR mode, you will be able to do CPR at your home or at centers, capture a video of yourself doing the CPR (Cardiopulmonary resuscitation), upload it to the application, wait for a full informative analysis of the results and how we detect your rate and depth of motion along with posture warnings. Also experience the real-time feature of CPR where you can use the application in case of emergencies, mount the mobile in a portatit mode, then start your live stream, and you are good to go.
+
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## Technical Setup
+
+This backend is built using FastAPI python framwork,it can be runned locally and it is also deployed on hugging face.
+
+
+# Instructions
+
+It is easier to access this backend through its deployed version on hugging face via docker through this base url for most of the applicaiton feature, this includes: SKin Burns, ECG Analysis and CPR Education Mode.
+
+"https://husseinhadidy-deploy-el7a2ny-application.hf.space"
+
+But running real-time mode of CPR can be tried locally for latency concerns, as hugging face is a free contianer that has low specs, so real-time and socket connection is not tested on the deployed instance.
+
+You can use the requirments.txt  to install the  requirments needed and run using (Python 3.10):
+
+```bash
+
+uvicorn app:app --host 0.0.0.0 --port 8000
+
+```

app.py

@@ -320,7 +320,7 @@ def run_cpr_analysis(source, requested_fps, output_path):
     requested_fps = 30
     input_video = source
 
-    output_dir = r"D:\BackendGp\Deploy_El7a2ny_Application\CPRRealTime\outputs"
+    output_dir = r"CPRRealTime\outputs"
     os.makedirs(output_dir, exist_ok=True)
 
     video_output_path = os.path.join(output_dir, "output.mp4")
@@ -361,7 +361,7 @@ async def websocket_analysis(websocket: WebSocket):
         with analyzer_lock:
             if not analysis_started:
                 requested_fps = 30
-                output_path = r"D:\CPR\End to End\Code Refactor\output\output.mp4"
+                output_path = r"Output"
 
                 analyzer_thread = threading.Thread(
                     target=run_cpr_analysis,