Merge pull request #56 from augmentedstartups/installation_error_fix

added change for installation error
augmentedstartups · Feb 6, 2024 · 362e006 · 362e006
2 parents a60b317 + 2ada2ed
commit 362e006
Showing 1 changed file with 39 additions and 28 deletions.
diff --git a/README.md b/README.md
@@ -2,27 +2,25 @@
 
 [<img src="https://kajabi-storefronts-production.kajabi-cdn.com/kajabi-storefronts-production/file-uploads/themes/2151476941/settings_images/65d82-0d84-6171-a7e0-5aa180b657d5_Black_with_Logo.jpg" width="100%">](https://www.youtube.com/watch?v=K-VcpPwcM8k)
 
-
-
-
-
 #### Table of Contents
+
 1. Introduction
 2. Prerequisites
 3. Clone the Repo
 4. Installation
-    - [Linux](#4-installation)
-    - [Windows 10/11](#4-installation) 
-    - [MacOS](#4-installation) 
+   - [Linux](#4-installation)
+   - [Windows 10/11](#4-installation)
+   - [MacOS](#4-installation)
 5. Running AS-One
 6. [Sample Code Snippets](#6-sample-code-snippets)
 7. [Model Zoo](asone/linux/Instructions/Benchmarking.md)
 
 ## 1. Introduction
+
 ==UPDATE: YOLO-NAS is OUT==
 
 AS-One is a python wrapper for multiple detection and tracking algorithms all at one place. Different trackers such as `ByteTrack`, `DeepSORT` or `NorFair` can be integrated with different versions of `YOLO` with minimum lines of code.
-This python wrapper provides YOLO models in `ONNX`, `PyTorch` & `CoreML`  flavors. We plan to offer support for future versions of YOLO when they get released.
+This python wrapper provides YOLO models in `ONNX`, `PyTorch` & `CoreML` flavors. We plan to offer support for future versions of YOLO when they get released.
 
 This is One Library for most of your computer vision needs.
 
@@ -35,20 +33,21 @@ Watch the step-by-step tutorial
 ## 2. Prerequisites
 
 - Make sure to install `GPU` drivers in your system if you want to use `GPU` . Follow [driver installation](asone/linux/Instructions/Driver-Installations.md) for further instructions.
-- Make sure you have [MS Build tools](https://aka.ms/vs/17/release/vs_BuildTools.exe) installed in system if using windows. 
+- Make sure you have [MS Build tools](https://aka.ms/vs/17/release/vs_BuildTools.exe) installed in system if using windows.
 - [Download git for windows](https://git-scm.com/download/win) if not installed.
 
 ## 3. Clone the Repo
 
 Navigate to an empty folder of your choice.
 
-```git clone https://github.com/augmentedstartups/AS-One.git```
+`git clone https://github.com/augmentedstartups/AS-One.git`
 
 Change Directory to AS-One
 
-```cd AS-One```
+`cd AS-One`
 
 ## 4. Installation
+
 <details open>
 <summary>For Linux</summary>
 
@@ -58,12 +57,14 @@ source .env/bin/activate
 
 pip install numpy Cython
 pip install cython-bbox asone onnxruntime-gpu==1.12.1
+pip install typing_extensions==4.7.1
 pip install super-gradients==3.1.3
 # for CPU
 pip install torch torchvision
 # for GPU
 pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu113
 ```
+
 </details>
 
 <details>
@@ -72,11 +73,12 @@ pip install torch torchvision --extra-index-url https://download.pytorch.org/whl
 ```shell
 python -m venv .env
 .env\Scripts\activate
-pip install numpy Cython 
+pip install numpy Cython
 pip install lap
 pip install -e git+https://github.com/samson-wang/cython_bbox.git#egg=cython-bbox
 
 pip install asone onnxruntime-gpu==1.12.1
+pip install typing_extensions==4.7.1
 pip install super-gradients==3.1.3
 # for CPU
 pip install torch torchvision
@@ -86,6 +88,7 @@ pip install torch torchvision --extra-index-url https://download.pytorch.org/whl
 or
 pip install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio===0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
 ```
+
 </details>
 <details>
 <summary>For MacOS</summary>
@@ -100,6 +103,7 @@ pip install super-gradients==3.1.3
 # for CPU
 pip install torch torchvision
 ```
+
 </details>
 
 ## 5. Running AS-One
@@ -112,10 +116,10 @@ python main.py data/sample_videos/test.mp4
 
 ### Run in `Google Colab`
 
- <a href="https://drive.google.com/file/d/1xy5P9WGI19-PzRH3ceOmoCgp63K6J_Ls/view?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
-
+<a href="https://drive.google.com/file/d/1xy5P9WGI19-PzRH3ceOmoCgp63K6J_Ls/view?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
 
 ## 6. Sample Code Snippets
+
 <details>
 <summary>6.1. Object Detection</summary>
 
@@ -199,13 +203,16 @@ while True:
     if cv2.waitKey(25) & 0xFF == ord('q'):
         break
 ```
+
 </details>
 
 <details>
 <summary>6.1.2. Changing Detector Models </summary>
 
 Change detector by simply changing detector flag. The flags are provided in [benchmark](asone/linux/Instructions/Benchmarking.md) tables.
-* Our library now supports YOLOv5, YOLOv7, and YOLOv8 on macOS.
+
+- Our library now supports YOLOv5, YOLOv7, and YOLOv8 on macOS.
+
 ```python
 # Change detector
 detector = ASOne(detector=asone.YOLOX_S_PYTORCH, use_cuda=True)
@@ -226,7 +233,7 @@ detector = ASOne(detector=asone.YOLOV8L_MLMODEL)
 <details>
 <summary>6.2. Object Tracking </summary>
 
-Use tracker on sample video. 
+Use tracker on sample video.
 
 ```python
 import asone
@@ -243,7 +250,7 @@ filter_classes = ['person'] # set to None to track all classes
 # Get tracking function
 track = detect.track_video('data/sample_videos/test.mp4', output_dir='data/results', save_result=True, display=True, filter_classes=filter_classes)
 
-# Loop over track to retrieve outputs of each frame 
+# Loop over track to retrieve outputs of each frame
 for bbox_details, frame_details in track:
     bbox_xyxy, ids, scores, class_ids = bbox_details
     frame, frame_num, fps = frame_details
@@ -255,7 +262,7 @@ for bbox_details, frame_details in track:
 # Get tracking function
 track = detect.track_webcam(cam_id=0, output_dir='data/results', save_result=True, display=True, filter_classes=filter_classes)
 
-# Loop over track to retrieve outputs of each frame 
+# Loop over track to retrieve outputs of each frame
 for bbox_details, frame_details in track:
     bbox_xyxy, ids, scores, class_ids = bbox_details
     frame, frame_num, fps = frame_details
@@ -268,7 +275,7 @@ for bbox_details, frame_details in track:
 stream_url = 'rtsp://wowzaec2demo.streamlock.net/vod/mp4:BigBuckBunny_115k.mp4'
 track = detect.track_stream(stream_url, output_dir='data/results', save_result=True, display=True, filter_classes=filter_classes)
 
-# Loop over track to retrieve outputs of each frame 
+# Loop over track to retrieve outputs of each frame
 for bbox_details, frame_details in track:
     bbox_xyxy, ids, scores, class_ids = bbox_details
     frame, frame_num, fps = frame_details
@@ -296,8 +303,8 @@ detect = ASOne(tracker=asone.DEEPSORT, detector=asone.YOLOV7_PYTORCH, use_cuda=T
 # Change Detector
 detect = ASOne(tracker=asone.DEEPSORT, detector=asone.YOLOX_S_PYTORCH, use_cuda=True)
 ```
-</details>
 
+</details>
 
 Run the `asone/demo_detector.py` to test detector.
 
@@ -308,6 +315,7 @@ python -m asone.demo_detector data/sample_videos/test.mp4
 # run on cpu
 python -m asone.demo_detector data/sample_videos/test.mp4 --cpu
 ```
+
 </details>
 <details>
 <summary>6.3. Text Detection</summary>
@@ -325,12 +333,13 @@ import cv2
 img_path = 'data/sample_imgs/sample_text.jpeg'
 ocr = ASOne(detector=asone.CRAFT, recognizer=asone.EASYOCR, use_cuda=True) # Set use_cuda to False for cpu
 img = cv2.imread(img_path)
-results = ocr.detect_text(img) 
+results = ocr.detect_text(img)
 img = utils.draw_text(img, results)
 cv2.imwrite("data/results/results.jpg", img)
 ```
 
 Use Tracker on Text
+
 ```python
 import asone
 from asone import ASOne
@@ -344,7 +353,7 @@ detect = ASOne(tracker=asone.DEEPSORT, detector=asone.CRAFT, recognizer=asone.EA
 # Get tracking function
 track = detect.track_video('data/sample_videos/GTA_5-Unique_License_Plate.mp4', output_dir='data/results', save_result=True, display=True)
 
-# Loop over track to retrieve outputs of each frame 
+# Loop over track to retrieve outputs of each frame
 for bbox_details, frame_details in track:
     bbox_xyxy, ids, scores, class_ids = bbox_details
     frame, frame_num, fps = frame_details
@@ -378,11 +387,12 @@ import cv2
 img_path = 'data/sample_imgs/test2.jpg'
 pose_estimator = PoseEstimator(estimator_flag=asone.YOLOV8M_POSE, use_cuda=True) #set use_cuda=False to use cpu
 img = cv2.imread(img_path)
-kpts = pose_estimator.estimate_image(img) 
+kpts = pose_estimator.estimate_image(img)
 img = utils.draw_kpts(img, kpts)
 cv2.imwrite("data/results/results.jpg", img)
 ```
-* Now you can use Yolov8 and Yolov7-w6 for pose estimation. The flags are provided in [benchmark](asone/linux/Instructions/Benchmarking.md) tables.
+
+- Now you can use Yolov8 and Yolov7-w6 for pose estimation. The flags are provided in [benchmark](asone/linux/Instructions/Benchmarking.md) tables.
 
 ```python
 # Pose Estimation on video
@@ -410,9 +420,10 @@ Run the `asone/demo_pose_estimator.py` to test Pose estimation.
 
 </details>
 
-To setup ASOne using Docker follow instructions given in [docker setup](asone/linux/Instructions/Docker-Setup.md) 
+To setup ASOne using Docker follow instructions given in [docker setup](asone/linux/Instructions/Docker-Setup.md)
 
 # ToDo
+
 - [x] First Release
 - [x] Import trained models
 - [x] Simplify code even further
@@ -424,6 +435,6 @@ To setup ASOne using Docker follow instructions given in [docker setup](asone/li
 - [x] YOLO-NAS
 - [ ] SAM Integration
 
-|Offered By: |Maintained By:|
-|-------------|-------------|
-|[![AugmentedStarups](https://user-images.githubusercontent.com/107035454/195115263-d3271ef3-973b-40a4-83c8-0ade8727dd40.png)](https://augmentedstartups.com)|[![AxcelerateAI](https://user-images.githubusercontent.com/107035454/195114870-691c8a52-fcf0-462e-9e02-a720fc83b93f.png)](https://axcelerate.ai/)|
+| Offered By:                                                                                                                                                  | Maintained By:                                                                                                                                    |
+| ------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [![AugmentedStarups](https://user-images.githubusercontent.com/107035454/195115263-d3271ef3-973b-40a4-83c8-0ade8727dd40.png)](https://augmentedstartups.com) | [![AxcelerateAI](https://user-images.githubusercontent.com/107035454/195114870-691c8a52-fcf0-462e-9e02-a720fc83b93f.png)](https://axcelerate.ai/) |