add example

.gitignore

@@ -1,2 +1,3 @@
 .DS_Store
-*.pt
+*.pt
+Inference/

app.py

@@ -1,16 +1,44 @@
 import gradio as gr 
 from detection import app as detector
 from recognition import app_easyocr
+from PIL import Image
+import requests
+import os
+
+
+def recognize(img_arr = None, img_url = None):
+    if img_arr == None and img_url != None:
+        print('downloading image....')
+        img_arr = Image.open(requests.get(img_url, stream=True).raw)
+
+    if img_arr == None: 
+        print('choose image or type the url!')
+        return
 
-def recognize(img_arr):
     detections = detector.detect(img_arr)
     return img_arr, detections
 
 
+input_image = gr.Image(type="pil")
+input_text = gr.Textbox(lines=1, label='Or Image Url', placeholder="paste image url here...")
+output_img = gr.Image(type='pil')
+output_json = gr.JSON()
+
+# examples = gr.Examples([[os.path.join(os.path.dirname(__file__), "examples/annas_running.jpg"), 'https://storage.googleapis.com/runpage-uscentral.appspot.com/runpage/79226/eca79d20-b364-11e9-8b83-4794e55a590e.jpg']],
+#     inputs=[input_image, input_text],
+#     outputs=[output_img, output_json],
+#     fn=recognize,
+#     cache_examples=True)
+
 demo = gr.Interface(fn=recognize, 
-                    inputs=[gr.Image(type="pil")], 
-                    outputs=[gr.Image(type='pil'), 'json'], 
+                    inputs=[input_image, input_text], 
+                    outputs=[output_img, output_json], 
+                    # examples=examples,
                     description='BIB Race Number Recognition')
-demo.launch()  
+
+
+if __name__ == "__main__":
+    demo.launch()
+# demo.launch()  
 
 

detection/app.py

@@ -20,14 +20,16 @@ from detection.utils.torch_utils import select_device, load_classifier, time_syn
 from PIL import Image
 
 #downloading models
-def download_models():
+def download_model(url):
     download_urls = [
         'https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt',
         'https://gitlab.com/annasblackhat/bib-weight/-/raw/main/bib-best.pt',
         'https://gitlab.com/annasblackhat/bib-weight/-/raw/main/bib-best-v2.pt']
-    for url in download_urls:
-        if not os.path.exists(os.path.basename(url)):
-            os.system("wget " + url)
+           
+    filename = os.path.basename(url)           
+    if not os.path.exists(filename):
+        os.system("wget " + url)
+    return filename
 
 # os.system("wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt")
 # os.system("wget https://gitlab.com/annasblackhat/bib-weight/-/raw/main/bib-best.pt")
@@ -39,13 +41,19 @@ except:
     print('dir exist')
 
 
-weights_paths = {'V1': 'bib-best.pt', 'V2': 'bib-best-v2.pt'}
+weight_list = {
+    'V1': 'https://gitlab.com/annasblackhat/bib-weight/-/raw/main/bib-best.pt',
+    'V2': 'https://gitlab.com/annasblackhat/bib-weight/-/raw/main/bib-best-v2.pt'
+}
 
-download_models()
-def detect(img, weight = "V2"):
-    print('weight: ', weight)
+#download base model
+download_model('https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt')
+
+def detect(img, weight_version = "V2"):
+    print('weight: ', weight_version)
+    weight_path = download_model(weight_list[weight_version])
     parser = argparse.ArgumentParser()
-    parser.add_argument('--weights', nargs='+', type=str, default=weights_paths[weight], help='model.pt path(s)')
+    parser.add_argument('--weights', nargs='+', type=str, default=weight_path, help='model.pt path(s)')
     parser.add_argument('--source', type=str, default='Inference/', help='source')  # file/folder, 0 for webcam
     parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)')
     parser.add_argument('--conf-thres', type=float, default=0.25, help='object confidence threshold')