diff --git a/MisplaceAI/process_misplaced_manager/utils.py b/MisplaceAI/process_misplaced_manager/utils.py
index 7f6a32cd13556ef292decb1efd6bc6022b239ba9..dc1c3d450ca85ea3704b6c83dbd0496fa3b34664 100644
--- a/MisplaceAI/process_misplaced_manager/utils.py
+++ b/MisplaceAI/process_misplaced_manager/utils.py
@@ -1,23 +1,16 @@
# MisplaceAI/process_misplaced_manager/utils.py
from django.utils import timezone
-from .models import DailyDetectionLimit, DetectionLimitSetting
-
-def check_daily_limit(user, detection_type):
- limit_setting = DetectionLimitSetting.objects.first()
- if not limit_setting:
- limit_setting = DetectionLimitSetting.objects.create(daily_image_limit=10, daily_video_limit=5)
-
- detection_limit, created = DailyDetectionLimit.objects.get_or_create(user=user)
- detection_limit.reset_limits() # Ensure limits are reset if the day has changed
-
- if detection_type == 'image':
- if detection_limit.image_detection_count >= limit_setting.daily_image_limit:
- return False, limit_setting.daily_image_limit - detection_limit.image_detection_count
- elif detection_type == 'video':
- if detection_limit.video_detection_count >= limit_setting.daily_video_limit:
- return False, limit_setting.daily_video_limit - detection_limit.video_detection_count
- return True, limit_setting.daily_image_limit - detection_limit.image_detection_count if detection_type == 'image' else limit_setting.daily_video_limit - detection_limit.video_detection_count
+from .models import DailyDetectionLimit
+from PIL import Image, ExifTags
+import cv2
+from moviepy.editor import ImageSequenceClip
+from item_detector.utils import run_inference
+from placement_rules.utils import PlacementRules
+from results_viewer.utils import visualize_pil_misplaced_objects
+from django.conf import settings
+import numpy as np
+import os
def increment_detection_count(user, detection_type):
detection_limit = DailyDetectionLimit.objects.get(user=user)
@@ -26,3 +19,70 @@ def increment_detection_count(user, detection_type):
elif detection_type == 'video':
detection_limit.video_detection_count += 1
detection_limit.save()
+
+def correct_image_orientation(image_path):
+ try:
+ image = Image.open(image_path)
+ for orientation in ExifTags.TAGS.keys():
+ if ExifTags.TAGS[orientation] == 'Orientation':
+ break
+ exif = image._getexif()
+ if exif is not None:
+ orientation = exif.get(orientation)
+ if orientation == 3:
+ image = image.rotate(180, expand=True)
+ elif orientation == 6:
+ image = image.rotate(270, expand=True)
+ elif orientation == 8:
+ image = image.rotate(90, expand=True)
+ image.save(image_path)
+ except (AttributeError, KeyError, IndexError):
+ pass
+
+def process_video_for_misplaced_objects(video_path, frame_interval, frame_delay, detection_model, category_index):
+ cap = cv2.VideoCapture(video_path)
+ fps = int(cap.get(cv2.CAP_PROP_FPS))
+ misplaced_objects_all_frames = []
+ detected_objects_all_frames = []
+ frame_count = 0
+ annotated_frame_count = 1 # Start frame count from 1 for annotated frames
+ frame_interval_frames = frame_interval * fps
+ annotated_frames = []
+
+ while cap.isOpened():
+ ret, frame = cap.read()
+ if not ret:
+ break
+
+ if frame_count % frame_interval_frames == 0:
+ image_np = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+ # Convert the frame to PIL image
+ image_pil = Image.fromarray(image_np)
+
+ detected_objects = run_inference(detection_model, category_index, image_pil)
+
+ placement_rules = PlacementRules()
+ misplaced_objects = placement_rules.check_placement(detected_objects)
+
+ detected_objects_all_frames.append(detected_objects)
+ misplaced_objects_all_frames.append(misplaced_objects)
+
+ # Annotate the frame with bounding boxes, labels, and annotated frame number
+ annotated_image_pil = visualize_pil_misplaced_objects(image_pil, detected_objects, misplaced_objects, annotated_frame_count)
+ annotated_image_np = np.array(annotated_image_pil)
+ annotated_frames.append(annotated_image_np)
+
+ # Increment the annotated frame count
+ annotated_frame_count += 1
+
+ frame_count += 1
+
+ cap.release()
+
+ # Create a video with a specified delay between each frame
+ output_video_path = os.path.join(settings.MEDIA_ROOT, 'videos', os.path.basename(video_path).replace('.mp4', '_annotated.mp4'))
+ annotated_clip = ImageSequenceClip(annotated_frames, fps=1/frame_delay)
+ annotated_clip.write_videofile(output_video_path, fps=fps, codec='libx264', audio_codec='aac')
+
+ return detected_objects_all_frames, misplaced_objects_all_frames, output_video_path
diff --git a/MisplaceAI/process_misplaced_manager/views.py b/MisplaceAI/process_misplaced_manager/views.py
index 14918699cdb51cb52c7221227439e68ea3d2a07a..29ff42af2d27e8e345accd2bf0c2dbbba5851b7f 100644
--- a/MisplaceAI/process_misplaced_manager/views.py
+++ b/MisplaceAI/process_misplaced_manager/views.py
@@ -13,15 +13,10 @@ from results_viewer.utils import visualize_misplaced_objects, visualize_pil_misp
from django.core.files.base import ContentFile
import base64
import os
-from PIL import Image, ExifTags
import logging
-import cv2
from django.conf import settings
from django.http import JsonResponse, HttpResponse, Http404
-import numpy as np
-from moviepy.editor import VideoFileClip, ImageSequenceClip
-from .utils import increment_detection_count
-
+from .utils import increment_detection_count, correct_image_orientation, process_video_for_misplaced_objects
logger = logging.getLogger(__name__)
@@ -36,9 +31,6 @@ class UploadedImageViewSet(viewsets.ModelViewSet):
serializer_class = UploadedImageSerializer
permission_classes = [IsAuthenticated]
-
-# MisplaceAI/process_misplaced_manager/views.py
-
@api_view(['POST'])
@permission_classes([IsAuthenticated])
def normal_detection(request):
@@ -86,26 +78,6 @@ def normal_detection(request):
print(f"Error processing image: {str(e)}")
return Response({'error': str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
-
-def correct_image_orientation(image_path):
- try:
- image = Image.open(image_path)
- for orientation in ExifTags.TAGS.keys():
- if ExifTags.TAGS[orientation] == 'Orientation':
- break
- exif = image._getexif()
- if exif is not None:
- orientation = exif.get(orientation)
- if orientation == 3:
- image = image.rotate(180, expand=True)
- elif orientation == 6:
- image = image.rotate(270, expand=True)
- elif orientation == 8:
- image = image.rotate(90, expand=True)
- image.save(image_path)
- except (AttributeError, KeyError, IndexError):
- pass
-
@api_view(['GET'])
@permission_classes([IsAuthenticated])
def display_results(request, image_id):
@@ -184,7 +156,9 @@ def display_video_results(request, video_id):
print("Processing video at path:", video_path)
print(f"Frame interval: {frame_interval}, Frame delay: {frame_delay}")
- detected_objects, misplaced_objects, output_video_path = process_video_for_misplaced_objects(video_path, frame_interval, frame_delay)
+ detected_objects, misplaced_objects, output_video_path = process_video_for_misplaced_objects(
+ video_path, frame_interval, frame_delay, detection_model, category_index
+ )
# Delete the original uploaded video
if os.path.exists(video_path):
@@ -203,67 +177,6 @@ def display_video_results(request, video_id):
except Exception as e:
print(f"Error processing video results: {e}")
return JsonResponse({'error': str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
-
-
-
-def process_video_for_misplaced_objects(video_path, frame_interval, frame_delay):
- cap = cv2.VideoCapture(video_path)
- frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
- frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
- fps = int(cap.get(cv2.CAP_PROP_FPS))
- misplaced_objects_all_frames = []
- detected_objects_all_frames = []
- frame_count = 0
- annotated_frame_count = 1 # Start frame count from 1 for annotated frames
- frame_interval_frames = frame_interval * fps
- annotated_frames = []
-
- while cap.isOpened():
- ret, frame = cap.read()
- if not ret:
- break
-
- if frame_count % frame_interval_frames == 0:
- image_np = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-
- # Convert the frame to PIL image
- image_pil = Image.fromarray(image_np)
-
- detected_objects = run_inference(detection_model, category_index, image_pil)
-
- placement_rules = PlacementRules()
- misplaced_objects = placement_rules.check_placement(detected_objects)
-
- detected_objects_all_frames.append(detected_objects)
- misplaced_objects_all_frames.append(misplaced_objects)
-
- # Annotate the frame with bounding boxes, labels, and annotated frame number
- annotated_image_pil = visualize_pil_misplaced_objects(image_pil, detected_objects, misplaced_objects, annotated_frame_count)
- annotated_image_np = np.array(annotated_image_pil)
- annotated_frames.append(annotated_image_np)
-
- # Increment the annotated frame count
- annotated_frame_count += 1
-
- frame_count += 1
-
- cap.release()
-
- # Create a video with a specified delay between each frame
- output_video_path = os.path.join(settings.MEDIA_ROOT, 'videos', os.path.basename(video_path).replace('.mp4', '_annotated.mp4'))
- annotated_clip = ImageSequenceClip(annotated_frames, fps=1/frame_delay)
- annotated_clip.write_videofile(output_video_path, fps=fps, codec='libx264', audio_codec='aac')
-
- return detected_objects_all_frames, misplaced_objects_all_frames, output_video_path
-
-
-
-
-
-#################################################################################################
-################################## Delete Video/Images ##########################################
-
-
@api_view(['DELETE'])
@permission_classes([IsAuthenticated])