Added URL Functionality

.gitignore

@@ -1,5 +1,5 @@
 .ipynb_checkpoints
 flagged
-telecom_object_detection.ipynb
+*.ipynb
 .env
 *.png

app.py

@@ -1,27 +1,34 @@
-# AUTOGENERATED! DO NOT EDIT! File to edit: telecom_object_detection.ipynb.
+# AUTOGENERATED! DO NOT EDIT! File to edit: telecom_object_detection-Iteration_2.ipynb.
 
 # %% auto 0
 __all__ = ['title', 'css', 'urls', 'imgs', 'img_samples', 'fig2img', 'custom_vision_detect_objects', 'set_example_url',
            'set_example_image', 'detect_objects']
 
-# %% telecom_object_detection.ipynb 2
+# %% telecom_object_detection-Iteration_2.ipynb 2
 import gradio as gr
 import numpy as np
 import os
 import io
 
-import requests
+import requests, validators
 
 from pathlib import Path
 
-# %% telecom_object_detection.ipynb 6
+# %% telecom_object_detection-Iteration_2.ipynb 4
+############################################
+### This code is based and adapted from: 
+# https://github.com/MicrosoftLearning/AI-102-AIEngineer/blob/master/18-object-detection/Python/test-detector/test-detector.py
+# https://huggingface.co/spaces/Gradio-Blocks/Object-Detection-With-DETR-and-YOLOS/blob/main/app.py
+############################################
+
+# %% telecom_object_detection-Iteration_2.ipynb 7
 from azure.cognitiveservices.vision.customvision.prediction import CustomVisionPredictionClient
 from msrest.authentication import ApiKeyCredentials
 from matplotlib import pyplot as plt
 from PIL import Image, ImageDraw, ImageFont
 from dotenv import load_dotenv
 
-# %% telecom_object_detection.ipynb 11
+# %% telecom_object_detection-Iteration_2.ipynb 12
 def fig2img(fig):
     buf = io.BytesIO()
     fig.savefig(buf)
@@ -94,7 +101,7 @@ def custom_vision_detect_objects(image_file: Path):
     fig.savefig(outputfile)
     print('Resulabsts saved in ', outputfile)
 
-# %% telecom_object_detection.ipynb 15
+# %% telecom_object_detection-Iteration_2.ipynb 17
 title = """<h1 id="title">Telecom Object Detection with Azure Custom Vision</h1>"""
 
 css = '''
@@ -103,41 +110,42 @@ h1#title {
 }
 '''
 
-# %% telecom_object_detection.ipynb 16
-urls = ["https://c8.alamy.com/comp/J2AB4K/the-new-york-stock-exchange-on-the-wall-street-in-new-york-J2AB4K.jpg"]
+# %% telecom_object_detection-Iteration_2.ipynb 18
+urls = ["https://www.dropbox.com/s/y5bk8om5ucu46d3/747.jpg?dl=1"]
 imgs = [path.as_posix() for path in sorted(Path('images').rglob('*.jpg'))]
 img_samples = [[path.as_posix()] for path in sorted(Path('images').rglob('*.jpg'))]
 
-# %% telecom_object_detection.ipynb 17
+# %% telecom_object_detection-Iteration_2.ipynb 21
 def set_example_url(example: list) -> dict:
+    print(gr.Textbox.update(value=example[0]))
     return gr.Textbox.update(value=example[0])
 
 def set_example_image(example: list) -> dict:
     return gr.Image.update(value=example[0])
 
-def detect_objects(image_input:Image):
-    #if validators.url(url_input):
-    #    image = Image.open(requests.get(url_input, stream=True).raw)
-    #elif image_input:
-    #    image = image_input
-    print(image_input)
-    print(image_input.size)
-    w, h = image_input.size
+def detect_objects(url_input:str, image_input:Image):
+    print(f"{url_input=}")
+    if validators.url(url_input):
+        image = Image.open(requests.get(url_input, stream=True).raw)
+    elif image_input:
+        image = image_input
+        
+    print(image)
+    print(image.size)
+    w, h = image.size
     
     if max(w, h) > 1_200:
         factor = 1_200 / max(w, h)
         factor = 1
         size = (int(w*factor), int(h*factor))
-        image_input = image_input.resize(size, resample=Image.Resampling.BILINEAR)
+        image = image.resize(size, resample=Image.Resampling.BILINEAR)
     
     resized_image_path = "input_object_detection.jpg"
-    image_input.save(resized_image_path)
+    image.save(resized_image_path)
     
-    #return image_input
-    #return custom_vision_detect_objects(Path(filename[0]))
     return custom_vision_detect_objects(resized_image_path)
 
-# %% telecom_object_detection.ipynb 19
+# %% telecom_object_detection-Iteration_2.ipynb 23
 with gr.Blocks(css=css) as demo:
     
     gr.Markdown(title)
@@ -166,8 +174,8 @@ with gr.Blocks(css=css) as demo:
                 example_url = gr.Dataset(components=[url_input], samples=[[str(url)] for url in urls])
             url_button = gr.Button("Detect")
             
-    url_button.click(detect_objects, inputs=[url_input], outputs=img_output_from_url)
-    image_button.click(detect_objects, inputs=[image_input], outputs=image_output)
+    url_button.click(detect_objects, inputs=[url_input,image_input], outputs=img_output_from_url)
+    image_button.click(detect_objects, inputs=[url_input,image_input], outputs=image_output)
     #image_button.click(detect_objects, inputs=[example_images], outputs=image_output)
     
     example_url.click(fn=set_example_url, inputs=[example_url], outputs=[url_input])

requirements.txt

@@ -1,2 +1,3 @@
 azure-cognitiveservices-vision-customvision==3.1.0
-python-dotenv==0.20.0
+python-dotenv==0.20.0
+validators