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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+examples/videos/example_video.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,10 +1,10 @@
 ---
-title: RSUD20K DEMO
-emoji: 📉
-colorFrom: gray
-colorTo: purple
+title: RSUD20K
+emoji: 🐢
+colorFrom: indigo
+colorTo: gray
 sdk: gradio
-sdk_version: 4.19.0
+sdk_version: 4.18.0
 app_file: app.py
 pinned: false
 ---

app.py

@@ -0,0 +1,83 @@
+import gradio as gr
+import cv2
+import requests
+import os
+from PIL import Image
+from ultralytics import YOLO
+
+
+################## MODEL ##################
+model = YOLO('best.pt')
+title = "RSUD20K"
+
+################## IMAGE ##################
+
+Image_directory = "examples/images"
+
+inputs_image = [
+    gr.components.Image(type="filepath", label="Input Image"),
+]
+outputs_image = [
+    gr.components.Image(type="numpy", label="Output Image"),
+]
+
+def show_preds_image(image_path):
+    image = cv2.imread(image_path)
+    outputs = model.predict(source=image_path)
+    results = Image.fromarray(outputs[0].plot()[:, :, ::-1])
+    return results
+
+    
+demo_image = gr.Interface(
+    fn=show_preds_image,
+    title=title,
+    inputs= inputs_image,
+    outputs= outputs_image,
+    examples= [os.path.join(Image_directory, fname) for fname in os.listdir(Image_directory) if fname.endswith(".jpg")],
+    allow_flagging="never",
+    analytics_enabled=False,
+)
+
+################## VIDEO ##################
+
+Video_directory = "examples/videos"
+
+inputs_video = [
+    gr.components.Video(label="Input Video"),
+]
+
+outputs_video = [
+    gr.components.Image(type = "numpy", label="Output Video"),
+]
+
+
+def show_preds_video(video_path):
+    cap = cv2.VideoCapture(video_path)
+    predicted_frames = []
+    while(cap.isOpened()):
+        ret, frame = cap.read()
+        if ret:
+            frame_copy = frame.copy()
+            outputs = model.predict(source=frame)
+            results = Image.fromarray(outputs[0].plot()[:, :, ::-1])
+            yield results
+        else:
+            break
+    cap.release()
+    cv2.destroyAllWindows()
+
+demo_video = gr.Interface(
+    fn=show_preds_video,
+    title=title,
+    inputs= inputs_video,
+    outputs= outputs_video,
+    examples= [os.path.join(Video_directory, fname) for fname in os.listdir(Video_directory) if fname.endswith(".mp4")],
+    allow_flagging="never",
+    analytics_enabled=False,
+)
+
+################## LAUNCH ##################
+gr.TabbedInterface(
+    [demo_image, demo_video],
+    tab_names=['Image inference', 'Video inference']
+).queue().launch()

best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ffe04bee563f192b59c1e2967357d7467a2396d63c8caacd80cc131677fe747c
+size 22504110

examples/videos/example_video.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:96ed84811e291de404333d4f1e6f9349c3836c0f5a3c134c366431340875d617
+size 4492700

requirements.txt

@@ -0,0 +1,47 @@
+# Ultralytics requirements
+# Usage: pip install -r requirements.txt
+
+# Base ----------------------------------------
+hydra-core>=1.2.0
+matplotlib>=3.2.2
+numpy>=1.18.5
+opencv-python>=4.1.1
+Pillow>=7.1.2
+PyYAML>=5.3.1
+requests>=2.23.0
+scipy>=1.4.1
+torch>=1.7.0
+torchvision>=0.8.1
+tqdm>=4.64.0
+ultralytics
+
+# Logging -------------------------------------
+tensorboard>=2.4.1
+# clearml
+# comet
+
+# Plotting ------------------------------------
+pandas>=1.1.4
+seaborn>=0.11.0
+
+# Export --------------------------------------
+# coremltools>=6.0  # CoreML export
+# onnx>=1.12.0  # ONNX export
+# onnx-simplifier>=0.4.1  # ONNX simplifier
+# nvidia-pyindex  # TensorRT export
+# nvidia-tensorrt  # TensorRT export
+# scikit-learn==0.19.2  # CoreML quantization
+# tensorflow>=2.4.1  # TF exports (-cpu, -aarch64, -macos)
+# tensorflowjs>=3.9.0  # TF.js export
+# openvino-dev  # OpenVINO export
+
+# Extras --------------------------------------
+ipython  # interactive notebook
+psutil  # system utilization
+thop>=0.1.1  # FLOPs computation
+# albumentations>=1.0.3
+# pycocotools>=2.0.6  # COCO mAP
+# roboflow
+
+# HUB -----------------------------------------
+GitPython>=3.1.24