Update app.py

app.py

@@ -52,62 +52,62 @@ chatgpt_chain = LLMChain(
 )
 
 #Helper function as this is what Pebblely API takes in
-def image_to_base64(img_path):
-    with open(img_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-#Removes backdrop from image using Pebblely API
-def removeBackdrop(image_path, output_path):
-    endpoint_url = "https://api.pebblely.com/remove-background/v1/"
-
-    response = requests.post(
-        endpoint_url,
-        headers={
-            "Content-Type": "application/json",
-            "X-Pebblely-Access-Token": os.environ["PEBBLELY_TOKEN"]
-        },
-        json={
-            "image": image_to_base64(image_path),
-        }
-    )
-    print(response)
-    image_b64 = response.json()["data"]
-    image_encoded = image_b64.encode("utf-8")
-    image_bytes = io.BytesIO(base64.b64decode(image_encoded))
-    image = Image.open(image_bytes)
-    image.save(output_path)
+# def image_to_base64(img_path):
+#     with open(img_path, "rb") as image_file:
+#         return base64.b64encode(image_file.read()).decode('utf-8')
+
+# #Removes backdrop from image using Pebblely API
+# def removeBackdrop(image_path, output_path):
+#     endpoint_url = "https://api.pebblely.com/remove-background/v1/"
+
+#     response = requests.post(
+#         endpoint_url,
+#         headers={
+#             "Content-Type": "application/json",
+#             "X-Pebblely-Access-Token": os.environ["PEBBLELY_TOKEN"]
+#         },
+#         json={
+#             "image": image_to_base64(image_path),
+#         }
+#     )
+#     print(response)
+#     image_b64 = response.json()["data"]
+#     image_encoded = image_b64.encode("utf-8")
+#     image_bytes = io.BytesIO(base64.b64decode(image_encoded))
+#     image = Image.open(image_bytes)
+#     image.save(output_path)
 
 #Takes the images from Pebblely output and generates images with different backdrops based on user prompts
-def DallEBackdropGen(image_path, prompt, n_img, size):
-    response = openai.Image.create_edit(
-      image=open(image_path, "rb"),
-      prompt=prompt,
-      n=n_img,
-      size=size
-    )
-    print(type(response))
-    print(response)
-    return response['data']
+# def DallEBackdropGen(image_path, prompt, n_img, size):
+#     response = openai.Image.create_edit(
+#       image=open(image_path, "rb"),
+#       prompt=prompt,
+#       n=n_img,
+#       size=size
+#     )
+#     print(type(response))
+#     print(response)
+#     return response['data']
 
 #Just outputs the images from DallE in a nice grid for easy consumption
-def outputGenImages(ori_image, response_data):
-    nrows = len(response_data)
-    # List of image URLs
-    image_urls = [response_data[i]['url'] for i in range(nrows)]
+# def outputGenImages(ori_image, response_data):
+#     nrows = len(response_data)
+#     # List of image URLs
+#     image_urls = [response_data[i]['url'] for i in range(nrows)]
 
-    # Load all the images into a list
-    images = [Image.open(BytesIO(requests.get(url).content)) for url in image_urls]
+#     # Load all the images into a list
+#     images = [Image.open(BytesIO(requests.get(url).content)) for url in image_urls]
 
-    # Create a new image of the right size
-    width, height = images[0].size  # assumes all images are the same size
-    total_height = height * nrows
-    new_im = Image.new('RGB', (width, total_height))
+#     # Create a new image of the right size
+#     width, height = images[0].size  # assumes all images are the same size
+#     total_height = height * nrows
+#     new_im = Image.new('RGB', (width, total_height))
 
-    # Paste in each image
-    for i, img in enumerate(images):
-        new_im.paste(img, (0, i * height))
+#     # Paste in each image
+#     for i, img in enumerate(images):
+#         new_im.paste(img, (0, i * height))
 
-    return new_im
+#     return new_im
 
 def upload_and_process(image, promptText, promptImg, lens_option, n_images, size):
     # We are assuming the removeBackdrop, DallEBackdropGen, outputGenImages are defined and available in your code
@@ -144,7 +144,7 @@ def upload_and_process(image, promptText, promptImg, lens_option, n_images, size
     # # Get and return the images
     # result_images = outputGenImages(image_path, response_data)
     
-    # text_output = f"<h2>{json.dumps(responses, indent=2)}</h2>"
+    text_output = f"<h2>{json.dumps(responses, indent=2)}</h2>"
     
     return text_output#, result_images  # Output should be a list of PIL Image objects or numpy arrays