handle request errors

Amr-YA · Nov 13, 2022 · 4fa8d2b · 4fa8d2b
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diff --git a/Dockerfile b/Dockerfile
@@ -1,16 +1,16 @@
-FROM python:3.9
-
-WORKDIR /app
-COPY ./requirements.txt .
-RUN pip install --upgrade pip
-RUN pip install -U wheel cmake
-RUN apt-get update && apt-get install -y python3-opencv
-RUN pip install opencv-python
-RUN pip install -r requirements.txt
-
-COPY . .
-
-EXPOSE 5005
-USER 1001
-
-CMD ["python", "./face_rec_code/app.py"]
+FROM python:3.9
+
+WORKDIR /app
+COPY ./requirements.txt .
+RUN pip install --upgrade pip
+RUN pip install -U wheel cmake
+RUN apt-get update && apt-get install -y python3-opencv
+RUN pip install opencv-python
+RUN pip install -r requirements.txt
+
+COPY . .
+
+EXPOSE 5005
+USER 1001
+
+CMD ["python", "./face_rec_code/app.py"]
diff --git a/changelog.md b/changelog.md
@@ -1,26 +1,26 @@
-# Changelog
-
-## 25-Sep-22 - git:feature-start_end
-1. added `video_face_rec.py/faces_split_timestamps` return value for all the enteries a faces appears
-2. added `video_face_rec.py/refine_results` to remove single frames faces from enteries return, but not activated in 1st appearance return
-3. fixed `timestamp` = 0 by the end of the video
-4. fixed `target_fps` having value less than 1 which resulted in corrupted video output
-
-## 24-Sep-22 - git:feature-custm_analysis
-1. restructured the files into folders
-    - `/face_rec_code/`: for all the python code
-    - `/face_rec_files/`: for the videos and pictures
-2. split the code into 2 python files
-    - `face_rec_code/video_face_rec.py` for loading the folder and files then the analysis code
-    - `face_rec_code/app.py` for running the flask server
-3. output unknown persons photos and labeled video are saved inside a folder by the name of the video inside `./unknown/`
-4. changed `video_face_rec.py/run` to `video_face_rec.py/pipeline` with default parameters in case no parameters passed 
-5. added 2 `app.py/run` methods in the server
-    - `app.py/run_defaults` - GET: uses the `video_face_rec.py/pipeline` with default parameters, doesn't take any arguments
-    - `app.py/run_custom` - POST: uses the `video_face_rec.py/pipeline` with customs parameters, takes the parameters from json object from the post request
-6. enhanced the `video_face_rec.py/confirm_dirs` to check all the directories and files are correct
-7. added `video_face_rec.py/fetch_video_full_dir` to get the video for the analysis (either from default or custom run)
-8. added tolerance parameter in the analysis
-9. moved code for saving photos and video to seperate functions `video_face_rec.py/save_photo` & `video_face_rec.py/save_video`
-10. changed the flask server running to more stable `app.py/WSGIServer`
+# Changelog
+
+## 25-Sep-22 - git:feature-start_end
+1. added `video_face_rec.py/faces_split_timestamps` return value for all the enteries a faces appears
+2. added `video_face_rec.py/refine_results` to remove single frames faces from enteries return, but not activated in 1st appearance return
+3. fixed `timestamp` = 0 by the end of the video
+4. fixed `target_fps` having value less than 1 which resulted in corrupted video output
+
+## 24-Sep-22 - git:feature-custm_analysis
+1. restructured the files into folders
+    - `/face_rec_code/`: for all the python code
+    - `/face_rec_files/`: for the videos and pictures
+2. split the code into 2 python files
+    - `face_rec_code/video_face_rec.py` for loading the folder and files then the analysis code
+    - `face_rec_code/app.py` for running the flask server
+3. output unknown persons photos and labeled video are saved inside a folder by the name of the video inside `./unknown/`
+4. changed `video_face_rec.py/run` to `video_face_rec.py/pipeline` with default parameters in case no parameters passed 
+5. added 2 `app.py/run` methods in the server
+    - `app.py/run_defaults` - GET: uses the `video_face_rec.py/pipeline` with default parameters, doesn't take any arguments
+    - `app.py/run_custom` - POST: uses the `video_face_rec.py/pipeline` with customs parameters, takes the parameters from json object from the post request
+6. enhanced the `video_face_rec.py/confirm_dirs` to check all the directories and files are correct
+7. added `video_face_rec.py/fetch_video_full_dir` to get the video for the analysis (either from default or custom run)
+8. added tolerance parameter in the analysis
+9. moved code for saving photos and video to seperate functions `video_face_rec.py/save_photo` & `video_face_rec.py/save_video`
+10. changed the flask server running to more stable `app.py/WSGIServer`
 11. analysis terminal prints are now in minutes & seconds, ex:"time:  0m:25s - Found 1 faces, recognized: Unknown"
diff --git a/face_rec_code/app.py b/face_rec_code/app.py
@@ -1,104 +1,104 @@
-import os
-from flask import Flask, request, jsonify
-import dlib
-from gevent.pywsgi import WSGIServer
-from video_face_rec import confirm_dirs, pipeline
-
-import warnings
-warnings.simplefilter("ignore")
-
-app = Flask(__name__)
-app.config['JSON_SORT_KEYS'] = False
-APP_DIR = os.path.dirname(__file__)
-DOCKER_DIR = os.path.dirname(APP_DIR)
-
-
-@app.route("/healthcheck", methods=["GET"])
-def healthcheck():
-    status, _, _, _, _, msg = confirm_dirs(DOCKER_DIR)
-    if status:
-        status_code = 200
-    else:
-        status_code = 425 # error in healthcheck
-    obj = {"status": msg}
-    return jsonify(obj), status_code
-
-@app.route("/run_defaults", methods=["GET"])
-def run_defaults():
-    print("-----default analysis running")
-    obj, status_code = pipeline()
-    return jsonify(obj), status_code
-
-@app.route("/run_custom", methods=["POST"])
-def run_custom():
-    print("-----custom analysis running")
-
-    try:
-        file_name = request.json["file_name"]
-        print("-----file name found in request: ", file_name)
-    except:
-        file_name = None
-        print("-----file name not found in request")
-
-    try:
-        model = request.json["model"]
-        print("-----model found in request: ", model)
-    except:
-        model = 'hog'
-        print("-----model name not found in request")
-
-    try:
-        skip_frames = request.json["skip_frames"]
-        print("-----skip_frames found in request: ", skip_frames)
-    except:
-        skip_frames = 5
-        print("-----skip_frames not found in request")
-
-    try:
-        resiz_factor = request.json["resiz_factor"]
-        print("-----resiz_factor found in request: ", resiz_factor)
-    except:
-        resiz_factor = 1
-        print("-----resiz_factor not found in request")
-
-    try:
-        n_upscale = request.json["n_upscale"]
-        print("-----n_upscale found in request: ", n_upscale)
-    except:
-        n_upscale = 1
-        print("-----n_upscale not found in request")
-
-    try:
-        num_jitters = request.json["num_jitters"]
-        print("-----num_jitters found in request: ", num_jitters)
-    except:
-        num_jitters = 1
-        print("-----num_jitters not found in request")
-
-    try:
-        tolerance = request.json["tolerance"]
-        print("-----tolerance found in request: ", tolerance)
-    except:
-        tolerance = 0.6
-        print("-----tolerance not found in request")
-
-    obj, status_code = pipeline(video_name=file_name, model=model, skip_frames=skip_frames, resiz_factor=resiz_factor, n_upscale=n_upscale, num_jitters=num_jitters, tolerance=tolerance)
-    return jsonify(obj), status_code
-
-
-
-if __name__ == "__main__":
-    print("-----working on: ",DOCKER_DIR)
-    try:
-        cuda = dlib.DLIB_USE_CUDA
-        if cuda:
-            print("-----running on GPU")
-        else:
-            print("-----running on CPU")
-    except:
-        print("-----couldnn't detect CUDA")
-
-    # app.run(debug=True, host="0.0.0.0", port="3000")
-
-    http_server = WSGIServer(('', 3000), app)
-    http_server.serve_forever()
+import os
+from flask import Flask, request, jsonify
+import dlib
+from gevent.pywsgi import WSGIServer
+from video_face_rec import confirm_dirs, pipeline
+
+import warnings
+warnings.simplefilter("ignore")
+
+app = Flask(__name__)
+app.config['JSON_SORT_KEYS'] = False
+APP_DIR = os.path.dirname(__file__)
+DOCKER_DIR = os.path.dirname(APP_DIR)
+
+
+@app.route("/healthcheck", methods=["GET"])
+def healthcheck():
+    status, _, _, _, _, msg = confirm_dirs(DOCKER_DIR)
+    if status:
+        status_code = 200
+    else:
+        status_code = 425 # error in healthcheck
+    obj = {"status": msg}
+    return jsonify(obj), status_code
+
+@app.route("/run_defaults", methods=["GET"])
+def run_defaults():
+    print("-----default analysis running")
+    obj, status_code = pipeline()
+    return jsonify(obj), status_code
+
+@app.route("/run_custom", methods=["POST"])
+def run_custom():
+    print("-----custom analysis running")
+
+    try:
+        file_name = request.json["file_name"]
+        print("-----file name found in request: ", file_name)
+    except:
+        file_name = None
+        print("-----file name not found in request")
+
+    try:
+        model = request.json["model"]
+        print("-----model found in request: ", model)
+    except:
+        model = 'hog'
+        print("-----model name not found in request")
+
+    try:
+        skip_frames = request.json["skip_frames"]
+        print("-----skip_frames found in request: ", skip_frames)
+    except:
+        skip_frames = 5
+        print("-----skip_frames not found in request")
+
+    try:
+        resiz_factor = request.json["resiz_factor"]
+        print("-----resiz_factor found in request: ", resiz_factor)
+    except:
+        resiz_factor = 1
+        print("-----resiz_factor not found in request")
+
+    try:
+        n_upscale = request.json["n_upscale"]
+        print("-----n_upscale found in request: ", n_upscale)
+    except:
+        n_upscale = 1
+        print("-----n_upscale not found in request")
+
+    try:
+        num_jitters = request.json["num_jitters"]
+        print("-----num_jitters found in request: ", num_jitters)
+    except:
+        num_jitters = 1
+        print("-----num_jitters not found in request")
+
+    try:
+        tolerance = request.json["tolerance"]
+        print("-----tolerance found in request: ", tolerance)
+    except:
+        tolerance = 0.6
+        print("-----tolerance not found in request")
+
+    obj, status_code = pipeline(video_name=file_name, model=model, skip_frames=skip_frames, resiz_factor=resiz_factor, n_upscale=n_upscale, num_jitters=num_jitters, tolerance=tolerance)
+    return jsonify(obj), status_code
+
+
+
+if __name__ == "__main__":
+    print("-----working on: ",DOCKER_DIR)
+    try:
+        cuda = dlib.DLIB_USE_CUDA
+        if cuda:
+            print("-----running on GPU")
+        else:
+            print("-----running on CPU")
+    except:
+        print("-----couldnn't detect CUDA")
+
+    # app.run(debug=True, host="0.0.0.0", port="3000")
+
+    http_server = WSGIServer(('', 3000), app)
+    http_server.serve_forever()
diff --git a/face_rec_code/request_test.py b/face_rec_code/request_test.py
@@ -1,21 +1,21 @@
-import requests
-
-# test the server requests
-port = "3000"
-post_obj = {
-            "file_name": "3.mp4",
-            # "model": "hog",
-            "skip_frames": 30,
-            # "resiz_factor": 1,
-            # "num_jitters": 1,
-            # "tolerance": 0.6,
-            }
-# method = "run_defaults"
-method = "run_custom"
-host = f'http://localhost:{port}/{method}'
-r = requests.post(host, json=post_obj)
-# r = requests.get(host)
-
-
-print(r.status_code)
-print(r.text)
+import requests
+
+# test the server requests
+port = "3000"
+post_obj = {
+            "file_name": "3.mp4",
+            # "model": "hog",
+            "skip_frames": 30,
+            # "resiz_factor": 1,
+            # "num_jitters": 1,
+            # "tolerance": 0.6,
+            }
+# method = "run_defaults"
+method = "run_custom"
+host = f'http://localhost:{port}/{method}'
+r = requests.post(host, json=post_obj)
+# r = requests.get(host)
+
+
+print(r.status_code)
+print(r.text)