computer vision 1

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import cv2
 import requests
 import os
-
+#pirahansiah/ComputerVision
 from ultralytics import YOLO
 
 file_urls = [
@@ -50,42 +50,42 @@ interface_image = gr.Interface(
     cache_examples=False,
 )
 
-def show_preds_video(video_path):
-    cap = cv2.VideoCapture(video_path)
-    while(cap.isOpened()):
-        ret, frame = cap.read()
-        if ret:
-            frame_copy = frame.copy()
-            outputs = model.predict(source=frame)
-            results = outputs[0].cpu().numpy()
-            for i, det in enumerate(results.boxes.xyxy):
-                cv2.rectangle(
-                    frame_copy,
-                    (int(det[0]), int(det[1])),
-                    (int(det[2]), int(det[3])),
-                    color=(0, 0, 255),
-                    thickness=2,
-                    lineType=cv2.LINE_AA
-                )
-            yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
+# def show_preds_video(video_path):
+#     cap = cv2.VideoCapture(video_path)
+#     while(cap.isOpened()):
+#         ret, frame = cap.read()
+#         if ret:
+#             frame_copy = frame.copy()
+#             outputs = model.predict(source=frame)
+#             results = outputs[0].cpu().numpy()
+#             for i, det in enumerate(results.boxes.xyxy):
+#                 cv2.rectangle(
+#                     frame_copy,
+#                     (int(det[0]), int(det[1])),
+#                     (int(det[2]), int(det[3])),
+#                     color=(0, 0, 255),
+#                     thickness=2,
+#                     lineType=cv2.LINE_AA
+#                 )
+#             yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
 
-inputs_video = [
-    gr.components.Video(type="filepath", label="Input Video"),
+# inputs_video = [
+#     gr.components.Video(type="filepath", label="Input Video"),
 
-]
-outputs_video = [
-    gr.components.Image(type="numpy", label="Output Image"),
-]
-interface_video = gr.Interface(
-    fn=show_preds_video,
-    inputs=inputs_video,
-    outputs=outputs_video,
-    title="Pothole detector",
-    examples=video_path,
-    cache_examples=False,
-)
+# ]
+# outputs_video = [
+#     gr.components.Image(type="numpy", label="Output Image"),
+# ]
+# interface_video = gr.Interface(
+#     fn=show_preds_video,
+#     inputs=inputs_video,
+#     outputs=outputs_video,
+#     title="Pothole detector",
+#     examples=video_path,
+#     cache_examples=False,
+# )
 
-gr.TabbedInterface(
-    [interface_image, interface_video],
-    tab_names=['Image inference', 'Video inference']
-).queue().launch()
+# gr.TabbedInterface(
+#     [interface_image, interface_video],
+#     tab_names=['Image inference', 'Video inference']
+# ).queue().launch()